CN105046077B - A kind of random physical perturbation motion method based on the conservation of energy - Google Patents

Abstract

The present invention relates to a random physical disturbance method based on energy conservation, which includes the following steps: 1) select the model for numerical prediction according to actual needs, and then determine the position of the final tendency item of each parameter in the model prediction equation; 2) after determining After the position of the parameter is determined, according to the disturbance form, the disturbance scheme of the tendency item is determined by integral, and the expression of the disturbance form is: , 3) Carry out two-dimensional Fourier decomposition of ε(t) in the horizontal direction, then filter out high-frequency noise and assign the coefficient of the wave with a wavelength of 1 to 4 times the grid distance to 0, and finally pass the adjusted coefficient through the inverse Fourier transform to synthesize new ε(t); 4) Repeat step 3) until the disturbance coefficient corresponding to each variable is obtained , and into the expression of the perturbed form. The beneficial effect is: the propensity perturbation is performed on completely independent physical processes, the purpose is to ensure the energy conservation of the propensity perturbation of the model variables, so that the method can improve the ensemble dispersion of the boundary layer model variables, which will significantly improve the storm-scale ensemble The forecast level of the forecast.

Description

A Random Physical Perturbation Method Based on Energy Conservation

technical field

The invention relates to the field of weather forecast, in particular to a random physical disturbance method based on energy conservation.

Background technique

A series of studies in the past have shown that storm-scale ensemble forecasting is feasible and effective, but the perturbation methods of various storm-scale ensemble forecasting systems still need to be perfected. For example, the storm-scale ensemble forecast system of the Center for Storm Analysis and Prediction (CAPS) in the United States can improve the forecast score by increasing the number of members and resolution, but its ensemble disturbance scheme is fixed, that is, the initial disturbance of each ensemble member adopts a fixed disturbance Amplitude, and matched with a specific physical scheme; the lateral boundary conditions of some ensemble members are provided by the short-term forecast of the NAM model, and the same lateral boundary conditions among members will limit the development of dispersion to a certain extent; on the other hand, the system does not consider Disturbance scale mismatch between side boundary disturbance and initial value disturbance. The typical problems mentioned above are reflected in all storm-scale ensemble forecast systems. The organic combination of initial value disturbance, physical (parameter) disturbance, side boundary disturbance and initial value disturbance all play an important role in the success of storm-scale ensemble forecast. play a key role in.

Because the evolution of the initial error over time is significantly different in baroclinic instability and convective instability, the initial disturbance constructed by the medium-term ensemble disturbance method cannot grow rapidly in the convective system, that is, the initial disturbance structure is not consistent with the development of the storm system. On the other hand, the incompatibility between the initial disturbance of the storm scale and the scale of the side boundary disturbance will also limit the growth of the initial disturbance and the dispersion of the ensemble. Multi-physics processes and multi-model ensembles help to improve the dispersion problem, but the precipitation forecast variables in the micro-physics scheme of the model and the threshold condition judgment of the micro-physics process are different, and have a significant impact on the precipitation intensity and fall area forecast. For different types of storm systems that occur in real time, it is blind to use a fixed set configuration to select different modes of microphysics schemes in combination.

Contents of the invention

The purpose of the present invention is to overcome the deficiencies of the above prior art, and provide a random physical disturbance method based on energy conservation, which is specifically realized by the following technical solutions:

The random physical disturbance method based on energy conservation comprises the steps of:

1) Select the ARPS model for numerical prediction according to actual needs, and then determine the position of the final tendency item output by each parameterization scheme in the model prediction equation;

2) After the position of the parameter is determined, according to the disturbance form, the disturbance scheme of the tendency item is determined by integral, the expression of the disturbance form is: X _P =(1+r _X )X _c ,

where X _c represents the time propensity term for all said parameters, X _p represents the time propensity term after perturbation, r _X represents the added perturbation, r _X autoregressive function of the form Where α is the decorrelation time scale, t indicates that the current mode time is t, ε(t) is a random number satisfying the uniform distribution, each time is generated using a different random seed, and the maximum and minimum values of the uniform distribution are set as 0.5 and -0.5, σ is the variance function of the disturbance, which changes with height, and the distribution shape is the same as the above-mentioned time tendency;

3) Carry out two-dimensional Fourier decomposition of ε(t) in the horizontal direction, and then filter out high-frequency noise and assign the coefficient of the wave with a wavelength of 1 to 4 times the grid spacing to 0, and finally pass the adjusted coefficient through inverse Fourier Transform and synthesize new ε(t);

4) Repeat step 3) until the disturbance coefficient r _X corresponding to each variable is obtained, and brought into the expression of the disturbance form, the variables include three wind field components u, v, w, a temperature variable T and a Water vapor variable qv.

The further design of the random physical disturbance method based on energy conservation is that the prediction equation of u is:

Among them, the time propensity term that can be disturbed is Indicates the time tendency of the u-variables output by the subgrid turbulence parameterization process. The remaining items cannot be disturbed, where (ρ*u) _t is the complete time tendency of the u variable, is the pressure gradient force term, -ADV(u) is the advection term, is the geostrophic deflection force term.

The further design of the random physical disturbance method based on energy conservation is that the prediction equation of the T is:

The propensity term that can be perturbed in the formula includes the subgrid turbulence parameterization process and propensity terms for diadiabatic processes for the microphysics and radiation schemes in Including the temperature tendency item output by the cumulus parameterization scheme and the temperature tendency item output by the radiation scheme; the remaining items cannot be disturbed, where (ρ*θ) _t is the complete time tendency item of potential temperature, is the convection term, and -ADV(θ') is the advection term of the potential temperature.

The further design of the random physical disturbance method based on energy conservation is that the prediction equation of the qv is:

The propensity term that can be perturbed in the formula includes the subgrid turbulence parameterization process and the propensity term for water vapor changes caused by the microphysics scheme The other terms cannot be disturbed, (ρ*q) _t is the complete time tendency term of water vapor, -ADV(q) is the advection term of water vapor, and (ρ*V _q q/z _ζ ) _ζ is the flux term of water vapor.

The advantages of the present invention are as follows:

The stochastic physical disturbance method based on energy conservation provided by the present invention performs tendency disturbance on completely independent physical processes, the purpose is to ensure the energy conservation of the tendency disturbance of model variables, so that the method can improve the internal mode including boundary layer and convection area The ensemble dispersion of variables will significantly improve the forecast level of storm-scale ensemble forecasts. Compared with the traditional perturbation to the complete time tendency, the perturbation scheme of the present invention can balance the perturbation added by the model itself, so that the total energy of the model will not change significantly (weather systems, especially when convective systems develop The factors that make it disappear, so when only a part of the physical process in the model is disturbed, other physical processes in the model will make corresponding adjustments, to a certain extent offset the energy introduced by human disturbance. The traditional scheme tends to carry out the complete time Disturbance makes the values of all physical processes uniformly magnified or reduced, so the conservation of energy cannot be guaranteed). At the same time, the disturbance scheme of the present invention can use different disturbance forms for different physical processes according to the characteristics of the process, making the disturbance more representative than traditional methods.

Detailed ways

Below in conjunction with accompanying drawing and specific embodiment, further clarifies the present invention, the random physical perturbation method based on energy conservation provided by the present invention mainly comprises:

1) Select the model for numerical prediction according to actual needs, and then determine the position of the final tendency item of each parameter in the model prediction equation;

2) After the position of the parameter is determined, according to the disturbance form, the disturbance scheme of the tendency item is determined by integral, the expression of the disturbance form is: X _p =(1+r _X )X _c ,

where X _c represents the time propensity term for all said parameters, X _p represents the time propensity term after perturbation, r _X represents the added perturbation, r _X autoregressive function of the form

Where ε(t) is a random number that satisfies the uniform distribution, which is generated using a different random seed each time, the maximum and minimum values of the uniform distribution are set to 0.5 and -0.5, and σ is the variance function of the disturbance, which varies with height , the distribution form is the same as that of the above-mentioned time tendency;

3) Carry out two-dimensional Fourier decomposition of ε(t) in the horizontal direction, and then filter out high-frequency noise and assign the coefficient of the wave with a wavelength of 1 to 4 times the grid spacing to 0, and finally pass the adjusted coefficient through inverse Fourier Transform and synthesize new ε(t);

4) Repeat step 3) until the disturbance coefficient r _X corresponding to each variable is obtained, and bring it into the expression of the disturbance form.

Provide the concrete implementation steps of above-mentioned method below:

(I.1) Select the model for numerical forecasting according to actual needs. This embodiment takes the ARPS model as an example.

(I.2) Determine the position of the final propensity term output by each parameterization scheme in the model forecast equation. The forecast equation of any model variable has multiple time bias items, and the final time bias of the variable is the sum of the above time bias items. The stochastic process only perturbs the time propensity term output by the parametric scheme. The prediction equation involved in the random disturbance includes three wind field components u, v, w, a temperature variable T, and a water vapor variable qv. The forms of u and v are similar, taking u as an example, the expression is as follows:

in Time tendency of the u-variables output by the subgrid turbulence parameterization process. Sure position in the program. In the same way, it is necessary to determine the v and w and s position.

The prediction equation of T is:

where the propensity term of the subgrid turbulence parameterization process is included and propensity terms for diadiabatic processes for the microphysics and radiation schemes in Including, but not limited to, the temperature propensity term output from the microphysics scheme and the temperature propensity term output from the radiation scheme. At least these two items should be perturbed. determined according to the model equation and position in the program.

The prediction equation of qv is:

Include a propensity term for the subgrid turbulence parameterization process and the propensity term for water vapor changes caused by the microphysics scheme Sure and position in the program.

(I.3) After determining the above and Then determine the disturbance scheme of these propensity items. The form of determining the disturbance is: X _p = (1+r _X ) X _c , where X _c represents the above seven time-inclined items, X _p represents the time-prone item after the disturbance, and r _X represents the added disturbance. X _p = (1+r _X ) X _c will be applied at each step of the integration.

(I.4) r _X is different in each step of integration. In order to ensure the randomness and continuity of r _X at the same time, an autoregressive function is used to determine the value of _rX in the next step of integration. The form of the autoregressive function is:

Among them, ε(t) is a random number that satisfies the uniform distribution, and is generated using a different random seed each time. The maximum and minimum values of the uniform distribution are set to 0.5 and -0.5. σ is the variance function of the disturbance, which varies with height, and the distribution shape is the same as that of the above-mentioned time tendency.

(I.5) Two-dimensional Fourier decomposition of ε(t) in the horizontal direction. Then assign the coefficient of the wave with a wavelength of 1-4 times the grid pitch to 0, which is used to filter out high-frequency noise. Then, the coefficient of the wavelength with small contribution is also assigned to be 0. Finally, the adjusted coefficients are synthesized into a new ε(t) through inverse Fourier transform.

(I.6) Perform (I.4) and (I.5) analysis on each variable to obtain the disturbance coefficient r _X of each variable itself.

(I.7) Use the r _X of each variable obtained in (I.6) to substitute into the disturbance equation of (I.3), and then apply this disturbance equation to each integral of different variables to complete the random What the physical process perturbation scheme does.

Claims (1)

1. a kind of random physical perturbation motion method based on the conservation of energy, it is characterised in that include the following steps：

1) the ARPS patterns for carrying out numerical forecast are selected, then determine that the output of parameters scheme is most in model predictions equation The position of tendency item eventually；

2) after the position of the parameter is determined further according to disturbance form the disturbance side for being inclined to item is determined by integrating Case, the expression formula for disturbing form are：X_p=(1+r_X)X_c,

Wherein X_cRepresentAndTime incline Xiang Xiang, X_pRepresent the time tendency item after disturbance, r_XRepresent coefficient of disturbance, r_XThe form of Autoregressive Functions is

Wherein α is decorrelation time scale, and t represents that the present mode moment is t, and ε (t) is the random number for meeting uniform distributions, Secondary when each to be generated using different random seeds, the maximum and minimum value of uniform distributions are set as 0.5 and -0.5, and σ is The variance function of disturbance, with height change, distributional pattern and the homomorphosis of tendency of above-mentioned time；

3) in the horizontal direction to ε (t) carry out two-dimension fourier decomposition, then filter out high-frequency noise by wherein 1 to 4 times of lattice away from The coefficient of the ripple of wavelength is assigned a value of 0, and the coefficient after adjustment is finally synthesized new ε (t) by inverse Fourier transform；

4) repeat step 3) until obtaining the corresponding coefficient of disturbance r of each variable_X, and bring into the expression formula of the disturbance form, The variable includes u, v, w, one temperature variable T of a three wind field components and steam variable qv；

The prognostic equation of u is：

<mfenced open = "" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mrow> <mo>(</mo> <mi>&amp;rho;</mi> <mo>*</mo> <mi>u</mi> <mo>)</mo> </mrow> <mi>t</mi> </msub> <mo>+</mo> <mi>m</mi> <mover> <mi>&amp;rho;</mi> <mo>&amp;OverBar;</mo> </mover> <msup> <mi>&amp;rho;</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>{</mo> <msub> <mrow> <mo>&amp;lsqb;</mo> <msub> <mi>J</mi> <mn>3</mn> </msub> <mrow> <mo>(</mo> <msup> <mi>p</mi> <mo>&amp;prime;</mo> </msup> <mo>-</mo> <msub> <mi>&amp;alpha;</mi> <mi>&amp;xi;</mi> </msub> <mi>D</mi> <mi>i</mi> <mi>v</mi> <mo>*</mo> <mo>)</mo> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mi>&amp;xi;</mi> </msub> <mo>+</mo> <msub> <mrow> <mo>&amp;lsqb;</mo> <msub> <mi>J</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <msup> <mi>p</mi> <mo>&amp;prime;</mo> </msup> <mo>-</mo> <msub> <mi>&amp;alpha;</mi> <mi>&amp;xi;</mi> </msub> <mi>D</mi> <mi>i</mi> <mi>v</mi> <mo>*</mo> <mo>)</mo> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mi>&amp;zeta;</mi> </msub> <mo>}</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mo>=</mo> <mo>-</mo> <mi>A</mi> <mi>D</mi> <mi>V</mi> <mrow> <mo>(</mo> <mi>u</mi> <mo>)</mo> </mrow> <mo>+</mo> <mi>&amp;rho;</mi> <mo>*</mo> <mo>&amp;lsqb;</mo> <mrow> <mo>(</mo> <mi>f</mi> <mo>+</mo> <msub> <mi>f</mi> <mi>m</mi> </msub> <mo>)</mo> </mrow> <mi>v</mi> <mo>-</mo> <mover> <mi>f</mi> <mo>&amp;OverBar;</mo> </mover> <mi>w</mi> <mo>-</mo> <msup> <mi>uwa</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>&amp;rsqb;</mo> <mo>+</mo> <msqrt> <mi>G</mi> </msqrt> <msub> <mi>D</mi> <mi>u</mi> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced>

Wherein can be disturbed time tendency item beRepresent the u variables of time grid turbulence parameterized procedure output when Between be inclined to, in the prognostic equation of u exceptIt is every cannot be disturbed, it is impossible to disturbed item includes the complete of u variables Time is inclined to (ρ * u)_t, pressure gradient-force itemAdvective term-ADV (u) and geostrophic deviating force item

The prognostic equation of v is：

<mfenced open = "" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mrow> <mo>(</mo> <mi>&amp;rho;</mi> <mo>*</mo> <mi>v</mi> <mo>)</mo> </mrow> <mi>t</mi> </msub> <mo>+</mo> <mi>m</mi> <mover> <mi>&amp;rho;</mi> <mo>&amp;OverBar;</mo> </mover> <msup> <mi>&amp;rho;</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>{</mo> <msub> <mrow> <mo>&amp;lsqb;</mo> <msub> <mi>J</mi> <mn>3</mn> </msub> <mrow> <mo>(</mo> <msup> <mi>p</mi> <mo>&amp;prime;</mo> </msup> <mo>-</mo> <msub> <mi>&amp;alpha;</mi> <mi>&amp;xi;</mi> </msub> <mi>D</mi> <mi>i</mi> <mi>v</mi> <mo>*</mo> <mo>)</mo> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mi>&amp;xi;</mi> </msub> <mo>+</mo> <msub> <mrow> <mo>&amp;lsqb;</mo> <msub> <mi>J</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <msup> <mi>p</mi> <mo>&amp;prime;</mo> </msup> <mo>-</mo> <msub> <mi>&amp;alpha;</mi> <mi>&amp;xi;</mi> </msub> <mi>D</mi> <mi>i</mi> <mi>v</mi> <mo>*</mo> <mo>)</mo> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mi>&amp;zeta;</mi> </msub> <mo>}</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mo>=</mo> <mo>-</mo> <mi>A</mi> <mi>D</mi> <mi>V</mi> <mrow> <mo>(</mo> <mi>v</mi> <mo>)</mo> </mrow> <mo>+</mo> <mi>&amp;rho;</mi> <mo>*</mo> <mo>&amp;lsqb;</mo> <mrow> <mo>(</mo> <mi>f</mi> <mo>+</mo> <msub> <mi>f</mi> <mi>m</mi> </msub> <mo>)</mo> </mrow> <mi>u</mi> <mo>-</mo> <mover> <mi>f</mi> <mo>&amp;OverBar;</mo> </mover> <mi>w</mi> <mo>-</mo> <msup> <mi>vwa</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>&amp;rsqb;</mo> <mo>+</mo> <msqrt> <mi>G</mi> </msqrt> <msub> <mi>D</mi> <mi>v</mi> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced>

Wherein can be disturbed time tendency item beRepresent the v variables of time grid turbulence parameterized procedure output when Between be inclined to, in the prognostic equation of v exceptIt is every cannot be disturbed, it is impossible to disturbed item includes the complete of v variables Time is inclined to (ρ * v)_t, pressure gradient-force itemAdvective term-ADV (v) and geostrophic deviating force item

The prognostic equation of w is：

<mfenced open = "" close = ""> <mtable> <mtr> <mtd> <mrow> <msub> <mrow> <mo>(</mo> <mi>&amp;rho;</mi> <mo>*</mo> <mi>w</mi> <mo>)</mo> </mrow> <mi>t</mi> </msub> <mo>+</mo> <mi>m</mi> <mover> <mi>&amp;rho;</mi> <mo>&amp;OverBar;</mo> </mover> <msup> <mi>&amp;rho;</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>{</mo> <msub> <mrow> <mo>&amp;lsqb;</mo> <msub> <mi>J</mi> <mn>3</mn> </msub> <mrow> <mo>(</mo> <msup> <mi>p</mi> <mo>&amp;prime;</mo> </msup> <mo>-</mo> <msub> <mi>&amp;alpha;</mi> <mi>&amp;xi;</mi> </msub> <mi>D</mi> <mi>i</mi> <mi>v</mi> <mo>*</mo> <mo>)</mo> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mi>&amp;xi;</mi> </msub> <mo>+</mo> <msub> <mrow> <mo>&amp;lsqb;</mo> <msub> <mi>J</mi> <mn>1</mn> </msub> <mrow> <mo>(</mo> <msup> <mi>p</mi> <mo>&amp;prime;</mo> </msup> <mo>-</mo> <msub> <mi>&amp;alpha;</mi> <mi>&amp;xi;</mi> </msub> <mi>D</mi> <mi>i</mi> <mi>v</mi> <mo>*</mo> <mo>)</mo> </mrow> <mo>&amp;rsqb;</mo> </mrow> <mi>&amp;zeta;</mi> </msub> <mo>}</mo> </mrow> </mtd> </mtr> <mtr> <mtd> <mrow> <mo>=</mo> <mo>-</mo> <mi>A</mi> <mi>D</mi> <mi>V</mi> <mrow> <mo>(</mo> <mi>w</mi> <mo>)</mo> </mrow> <mo>+</mo> <mi>&amp;rho;</mi> <mo>*</mo> <mo>&amp;lsqb;</mo> <mrow> <mo>(</mo> <mi>f</mi> <mo>+</mo> <msub> <mi>f</mi> <mi>m</mi> </msub> <mo>)</mo> </mrow> <mi>w</mi> <mo>-</mo> <mover> <mi>f</mi> <mo>&amp;OverBar;</mo> </mover> <mi>u</mi> <mo>-</mo> <msup> <mi>vwa</mi> <mrow> <mo>-</mo> <mn>1</mn> </mrow> </msup> <mo>&amp;rsqb;</mo> <mo>+</mo> <msqrt> <mi>G</mi> </msqrt> <msub> <mi>D</mi> <mi>w</mi> </msub> </mrow> </mtd> </mtr> </mtable> </mfenced>

Wherein can be disturbed time tendency item beRepresent the w variables of time grid turbulence parameterized procedure output when Between be inclined to, in the prognostic equation of w exceptIt is every cannot be disturbed, it is impossible to disturbed item includes the complete of w variables The whole time is inclined to (ρ * w)_t, pressure gradient-force itemAdvective term- ADV (w), and geostrophic deviating force item

The prognostic equation of the T is：

<mrow> <msub> <mrow> <mo>(</mo> <mi>&amp;rho;</mi> <mo>*</mo> <mi>&amp;theta;</mi> <mo>)</mo> </mrow> <mi>t</mi> </msub> <mo>+</mo> <mi>&amp;rho;</mi> <mo>*</mo> <mi>w</mi> <msub> <mover> <mi>&amp;theta;</mi> <mo>&amp;OverBar;</mo> </mover> <mi>x</mi> </msub> <mo>=</mo> <mo>-</mo> <mi>A</mi> <mi>D</mi> <mi>V</mi> <mrow> <mo>(</mo> <msup> <mi>&amp;theta;</mi> <mo>&amp;prime;</mo> </msup> <mo>)</mo> </mrow> <mo>+</mo> <msqrt> <mi>G</mi> </msqrt> <msub> <mi>D</mi> <mi>&amp;theta;</mi> </msub> <mo>+</mo> <msqrt> <mi>G</mi> </msqrt> <msub> <mi>S</mi> <mi>&amp;theta;</mi> </msub> <mo>,</mo> </mrow>

The tendency item for including time grid turbulence parameterized procedure that can be disturbed in formulaWith Microphysical scheme and radiation The tendency item of the nonadiabatic process of schemeWhereinIncluding the temperature tendency item of Microphysical scheme output and radiation The temperature tendency item of scheme output；Removed in the prognostic equation of TWithOuter items cannot be disturbed, it is impossible to is disturbed Dynamic item includes the full time tendency item (ρ * θ) of position temperature_t, convective termAnd advective term-the ADV (θ ') of position temperature；

The prognostic equation of the qv is：

<mrow> <msub> <mrow> <mo>(</mo> <mi>&amp;rho;</mi> <mo>*</mo> <mi>q</mi> <mo>)</mo> </mrow> <mi>t</mi> </msub> <mo>=</mo> <mo>-</mo> <mi>A</mi> <mi>D</mi> <mi>V</mi> <mrow> <mo>(</mo> <mi>q</mi> <mo>)</mo> </mrow> <mo>+</mo> <msub> <mrow> <mo>(</mo> <mi>&amp;rho;</mi> <mo>*</mo> <msub> <mi>V</mi> <mi>q</mi> </msub> <mi>q</mi> <mo>/</mo> <msub> <mi>z</mi> <mi>&amp;zeta;</mi> </msub> <mo>)</mo> </mrow> <mi>&amp;zeta;</mi> </msub> <mo>+</mo> <msqrt> <mi>G</mi> </msqrt> <msub> <mi>D</mi> <mi>q</mi> </msub> <mo>+</mo> <msqrt> <mi>G</mi> </msqrt> <msub> <mi>S</mi> <mi>q</mi> </msub> </mrow>

The tendency item for including time grid turbulence parameterized procedure that can be disturbed in formulaCaused by Microphysical scheme The tendency item of steam changeIn the prognostic equation of qv exceptItems cannot be disturbed, it is impossible to disturbed item Full time tendency item (ρ * q) including steam_t, the advective term-ADV (q) of steam, flux term (the ρ * V of steam_qq/z_ζ)_ζ。