Method for calculating uniformity degree of volume clamping and mixing process in cloud based on remote sensing means

Abstract

The invention relates to the field of atmospheric science, and discloses a method for calculating the uniformity degree of a coil-clamping mixing process in cloud based on a remote sensing means, and the method comprises the steps: building a function relation between a parameter b and a uniform mixing degree psi in a radar reflectivity factor and water content function relation (Z-LWC) based on a high-resolution numerical mode; according to the radar reflectivity factor output by the cloud radar and the inverted water content, a Z-LWC relation based on remote sensing observation is established, and the value of a parameter b is obtained; according to the value of the parameter b obtained through remote sensing observation, the function relation between the parameter b and the psi obtained through the numerical mode is combined, and the uniform mixing degree of the coil clamping mixing process is calculated. According to the invention, the observation and research of the clip-coil mixing process can be expanded from expensive and discontinuous aircraft observation data to economic, continuous and widely used remote sensing observation data, the limitation of the conventional research method is broken through, new means for the observation and research of the clip-coil mixing process are added, and the research efficiency of the clip-coil mixing process is improved.

Description

Technical Field

[0001] The invention relates to the field of atmospheric science, and in particular to a method for calculating the uniformity of an entrainment and mixing process in a cloud based on remote sensing means. Background Art

[0002] Clouds are an important part of the Earth system. Changes in the macroscopic and microscopic physical properties of clouds directly affect the radiation balance, atmospheric movement and water distribution of the Earth system, and thus affect weather and climate. Atmospheric numerical model results show that a 2-micron reduction in the effective radius of cloud droplets can offset the impact of a doubling of carbon dioxide concentration. Among the microphysical processes related to clouds, the turbulent entrainment and mixing process between clouds and ambient air has an important influence on the macroscopic and microscopic physical properties of clouds. Different degrees of entrainment and mixing in this process correspond to different cloud microphysical characteristics. In the uniform entrainment and mixing mechanism, all cloud droplets in the cloud are in almost the same supersaturated / unsaturated environment, and cloud droplets of all sizes partially evaporate, resulting in a decrease in the size of cloud droplets, but the number concentration of cloud droplets does not change. In the inhomogeneous entrainment and mixing mechanism, cloud droplets in contact with dry air evaporate, and cloud droplets that are not in contact with ambient air are not affected. In extreme cases, cloud droplets in contact with ambient air evaporate completely, saturating the ambient air, resulting in a decrease in the number concentration of cloud droplets and unchanged cloud droplet size. At this time, the mechanism is called an extreme inhomogeneous entrainment and mixing mechanism. Grabowski 2006 and Slawinska 2008 found through cloud resolution model (CRM) and large eddy model (LES) studies that the solar radiation reaching the ground in clean clouds and polluted clouds assuming uniform entrainment and mixing mechanisms and inhomogeneous entrainment and mixing mechanisms, respectively, is almost equal, indicating that the entrainment and mixing mechanism has an important influence on the radiation characteristics of clouds.

[0003] Atmospheric numerical models are an important way to study weather and climate. Accurately describing the entrainment and mixing mechanism in atmospheric numerical models is crucial to the accuracy of model forecasts, and is conducive to improving the model's simulation capabilities for cloud physics, precipitation, and cloud-climate feedback. However, the entrainment and mixing process occurs at a sub-grid scale, and the resolution of atmospheric numerical models is insufficient to resolve the process, so it can only be described in atmospheric numerical models through parameterization schemes.

[0004] At present, observational studies on the entrainment and mixing mechanism are limited to the use of aircraft observation data. Although aircraft sampling is the most direct means to observe cloud microphysics and dynamic characteristics, aircraft observations are restricted by the high cost of detectors, low sampling frequency, small sampling volume, and many uncertainties when aircraft perform field observation missions. Therefore, aircraft cannot conduct continuous spatial and temporal observations of clouds, which seriously hinders further research on the entrainment and mixing mechanism. The development of radar detection technology has enabled cloud radar to be widely used in the study of macroscopic and microscopic physical properties of remotely sensed clouds. Cloud radar can continuously observe clouds with high spatial and temporal resolution. However, there is currently no method for using cloud radar data to remotely sense the entrainment and mixing process in clouds. Therefore, if a method can be established to study the entrainment and mixing process using cloud radar observation data, it will be an important progress in studying the entrainment and mixing process through observational data. Summary of the invention

[0005] The purpose of the present invention is to overcome the shortcomings of the prior art and provide a method for calculating the uniformity of the cloud entrainment and mixing process based on remote sensing means, comprising the following steps:

[0006] Step 1, establish the functional relationship between parameters b and ψ in the Z-LWC functional relationship based on the high-resolution numerical model;

[0007] Step 2: According to the radar reflectivity factor output by the cloud radar and the inverted water content, a Z-LWC relationship based on remote sensing observations is established to obtain the value of parameter b;

[0008] Step three, based on the value of parameter b obtained from remote sensing observations and the functional relationship between parameter b and ψ obtained from the numerical model, the degree of uniform mixing in the entrainment mixing process is obtained.

[0009] Furthermore, the establishment of the functional relationship between the parameters b and ψ in the Z-LWC functional relationship based on the high-resolution numerical model includes:

[0010] The high-resolution entrainment and mixing model is driven by the meteorological element sounding observation data, and the entrainment and mixing cases are simulated by setting different factors affecting the entrainment and mixing process. The b-ψ function relationship is established for the entrainment and mixing cases where the clouds do not completely dissipate after the entrainment and mixing process.

[0011] The factors affecting the entrainment and mixing process include the initial cloud droplet concentration, the proportion of ambient air involved, the turbulent kinetic energy dissipation rate and the height at which the entrainment process occurs; the criterion for determining whether the cloud has not completely dissipated is that the water content is greater than 0.001 gm -3 And the cloud droplet concentration is greater than 10cm -3 ; The ψ is the degree of uniform mixing;

[0012] Furthermore, the b-ψ function relationship is established for the entrainment mixing case where the cloud does not completely dissipate after the entrainment mixing process, including:

[0013] According to the cloud droplet spectrum output by the entrainment mixing model, the radar reflectivity factor is calculated using the following formula:

[0014] Z = ∫ N (D) D 6 dD

[0015] Where Z is the radar reflectivity factor, D is the diameter of the droplet, and N(D) is the concentration of cloud droplets in the unit D interval; cloud microphysical quantities are calculated based on the cloud droplet spectrum output by the entrainment mixing mode. The cloud microphysical quantities include water content LWC, cloud droplet number concentration n c , volume mean radius r v ;

[0016] According to the Z-LWC function form, the value of parameter b in the function form is obtained:

[0017] Z=a*LWC b

[0018] Among them, parameters a and b are constants; the instantaneous Z and LWC values ​​of each case in the process of entrainment and mixing are fitted using the Z-LWC function form to obtain the parameter b of the entrainment and mixing case;

[0019] According to the cloud microphysical quantities of the entrainment mixing case, ψ is obtained:

[0020]

[0021]

[0022] Among them, n a 、r va , LWC a are the cloud droplet number concentration, volume mean radius and water content in the adiabatic cloud, respectively. n0 and LWC0 are the cloud droplet number concentration and water content before evaporation after entrainment, respectively, and n0 can also be considered as the number concentration under the uniform mixing mechanism; n i is the number concentration under the extremely inhomogeneous mixing mechanism, n c is the number concentration during the entrainment mixing process, r vh is the volume average radius after uniform mixing, ρ w is the density of water, LWC f It is the water content of the cloud when it reaches a new equilibrium state during the mixing and evaporation process;

[0023] According to the combination of parameters b and ψ of the entrainment mixing case, the functional relationship between parameters b and ψ is established:

[0024] ψ=1.11*[1-exp(-2.71*(b-1))].

[0025] Furthermore, the Z-LWC relationship based on remote sensing observation is established according to the base data output by the cloud radar and the water content inversion result to obtain the value of the parameter b, including:

[0026] The radar reflectivity factor is obtained based on the basic data output by the cloud radar; the water content in the cloud is obtained based on the method of inverting water content by the cloud radar;

[0027] If the cloud radar is a single polarization cloud radar, the water content is:

[0028]

[0029]

[0030] Among them, r0 is the distance from the radar to the cloud bottom, r i is the i-th distance from the cloud base, r T is the distance to the cloud top, K is the mass absorption coefficient, b is the parameter b in the Z-LWC function relationship, Z m is the reflectivity factor of radar observation, LWP is the cloud water path;

[0031] If the cloud radar is a dual polarization cloud radar, the water content is:

[0032]

[0033] DFR = dBZ f1 -dBZ f2

[0034] Among them, A l , A g are the absorption coefficients of liquid water and gas respectively, r is the distance, dBZ is the radar echo intensity, f1 and f2 are the frequencies of the dual-wavelength radar respectively.

[0035] Furthermore, the uniform mixing degree of the entrainment mixing process is obtained according to the obtained value of the parameter b and the functional relationship between the obtained parameter b and ψ, including:

[0036] The parameter b obtained from remote sensing observation data is used as the independent variable and substituted into the b-ψ function relationship to quantitatively calculate ψ, thereby obtaining the uniform mixing degree of the cloud entrainment mixing process based on remote sensing observation data.

[0037] The beneficial effects of the present invention are as follows: the present invention utilizes a high-resolution entrainment and mixing model specially developed for studying the entrainment and mixing process to perform a large number of entrainment and mixing case simulations, and first establishes a functional relationship between the parameters b and ψ in the Z-LWC functional relationship (i.e., the b-ψ relationship) through the changes in the microphysical quantities in the entrainment and mixing process. Afterwards, the parameter b obtained through remote sensing observation data is substituted into the b-ψ relationship to calculate ψ, thereby realizing the quantitative calculation of the uniformity of the entrainment and mixing process through remote sensing means. The method combines high-resolution numerical models with remote sensing observation data, and can realize the expansion of the observation and research of the entrainment and mixing process from expensive, discontinuous aircraft observation data to economical, continuous, and widely used remote sensing observation data, breaking through the limitations of previous observation and research methods of the process, having strong adaptability, and adding a new means to the observation and research of the entrainment and mixing process, thereby improving the efficiency of the entrainment and mixing process research. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 Schematic diagram of the main steps of implementing this method;

[0039] Figure 2 A flowchart of the specific steps for implementing this method;

[0040] Figure 3 It is a schematic diagram of high-resolution entrainment and mixing mode;

[0041] Figure 4 This is a graph showing the functional relationship (b-ψ) between the parameter b and the degree of uniform mixing based on the high-resolution entrainment mixing model. DETAILED DESCRIPTION

[0042] The technical solution of the present invention is further described in detail below in conjunction with the accompanying drawings, but the protection scope of the present invention is not limited to the following.

[0043] The features and properties of the present invention are further described in detail below with reference to examples.

[0044] like Figure 1 As shown, a method for calculating the uniformity of cloud entrainment and mixing process based on remote sensing means includes the following steps:

[0045] Step 1, establish the functional relationship between parameters b and ψ in the Z-LWC functional relationship based on the high-resolution numerical model;

[0046] Step 2: According to the radar reflectivity factor output by the cloud radar and the inverted water content, the Z-LWC relationship based on remote sensing observations is established, and the value of parameter b is obtained;

[0047] Step three, based on the value of parameter b obtained from remote sensing observations and the functional relationship between parameter b and ψ obtained from the numerical model, the degree of uniform mixing in the entrainment mixing process is obtained.

[0048] The establishment of the functional relationship between the parameters b and ψ in the Z-LWC functional relationship based on the high-resolution numerical model includes:

[0049] The high-resolution entrainment and mixing model is driven by the meteorological element sounding observation data, and the entrainment and mixing cases are simulated by setting different factors affecting the entrainment and mixing process. The b-ψ function relationship is established for the entrainment and mixing cases where the clouds do not completely dissipate after the entrainment and mixing process.

[0050] The factors affecting the entrainment and mixing process include the initial cloud droplet concentration, the proportion of ambient air involved, the turbulent kinetic energy dissipation rate and the height at which the entrainment process occurs; the criterion for determining whether the cloud has not completely dissipated is that the water content is greater than 0.001 gm -3 And the cloud droplet concentration is greater than 10cm -3 ; The ψ is the degree of uniform mixing;

[0051] The b-ψ function relationship is established for the entrainment mixing case where the cloud does not completely dissipate after the entrainment mixing process, including:

[0052] According to the cloud droplet spectrum output by the entrainment mixing model, the radar reflectivity factor is calculated using the following formula:

[0053] Z = ∫ N (D) D 6 dD

[0054] Where Z is the radar reflectivity factor, D is the diameter of the droplet, and N(D) is the concentration of cloud droplets in the unit D interval; cloud microphysical quantities are calculated based on the cloud droplet spectrum output by the entrainment mixing mode. The cloud microphysical quantities include water content LWC, cloud droplet number concentration n c , volume mean radius r v ;

[0055] According to the Z-LWC function form, the value of parameter b in the function form is obtained:

[0056] Z=a*LWC b

[0057] Among them, parameters a and b are constants; the instantaneous Z and LWC values ​​of each case in the process of entrainment and mixing are fitted using the Z-LWC function form to obtain the parameter b of the entrainment and mixing case;

[0058] According to the cloud microphysical quantities of the entrainment mixing case, ψ is obtained:

[0059]

[0060]

[0061] Among them, n a 、r va , LWC a are the cloud droplet number concentration, volume mean radius and water content in the adiabatic cloud, respectively. n0 and LWC0 are the cloud droplet number concentration and water content before evaporation after entrainment, respectively, and n0 can also be considered as the number concentration under the uniform mixing mechanism; n i is the number concentration under the extremely inhomogeneous mixing mechanism, n c is the number concentration during the entrainment mixing process, r vh is the volume average radius after uniform mixing, ρ w is the density of water, LWC f It is the water content of the cloud when it reaches a new equilibrium state during the mixing and evaporation process;

[0062] According to the combination of parameters b and ψ of the entrainment mixing case, the functional relationship between parameters b and ψ is established:

[0063] ψ=1.11*[1-exp(-2.71*(b-1))]

[0064] The above-mentioned method of establishing a Z-LWC relationship based on remote sensing observations based on the base data output by the cloud radar and the water content inversion result to obtain the value of the parameter b includes:

[0065] The radar reflectivity factor is obtained based on the basic data output by the cloud radar; the water content in the cloud is obtained based on the method of inverting water content by the cloud radar;

[0066] If the cloud radar is a single polarization cloud radar, the water content is:

[0067]

[0068]

[0069] Among them, r0 is the distance from the radar to the cloud bottom, r i is the i-th distance from the cloud base, r T is the distance to the cloud top, K is the mass absorption coefficient, b is the parameter b in the Z-LWC function relationship, Z m is the reflectivity factor of radar observation, LWP is the cloud water path;

[0070] If the cloud radar is a dual polarization cloud radar, the water content is:

[0071]

[0072] DFR = dBZ f1 -dBZ f2

[0073] Among them, A l , Ag are the absorption coefficients of liquid water and gas respectively, r is the distance, dBZ is the radar echo intensity, f1 and f2 are the frequencies of the dual-wavelength radar respectively.

[0074] The value of the parameter b obtained from remote sensing observations is combined with the functional relationship between the parameter b and ψ obtained from the numerical model to obtain the uniform mixing degree of the entrainment mixing process, including:

[0075] The parameter b obtained from remote sensing observation data is used as the independent variable and substituted into the b-ψ function relationship to quantitatively calculate ψ, thereby obtaining the uniform mixing degree of the cloud entrainment mixing process based on remote sensing observation data.

[0076] Specifically, the technical solution adopted by the present invention is: first, a high-resolution entrainment and mixing model is used to simulate a large number of entrainment and mixing cases, and the cloud droplet spectrum output by the model is used to calculate the radar reflectivity factor (Z) and the cloud water content (LWC), and a Z-LWC functional relationship based on the numerical model is established. Secondly, the parameter b in the Z-LWC relationship of the model is combined with ψ calculated by the cloud droplet spectrum to establish a functional relationship between b and ψ (i.e., the b-ψ relationship); thirdly, cloud radar remote sensing observation means are used to obtain the radar reflectivity factor and cloud water content, and a Z-LWC functional relationship based on remote sensing observation is established; finally, the parameter b in the remote sensing Z-LWC relationship is used as an independent variable, and is substituted into the b-ψ relationship to calculate the ψ value, so as to realize the calculation of the uniform mixing degree of the entrainment and mixing process by remote sensing observation means, and break through the limitation that the observation and research of the entrainment and mixing process is limited to aircraft observation data. The specific steps include:

[0077] (1) Establishing the b-ψ functional relationship based on numerical simulation: First, a high-resolution entrainment mixing model is used to set up a large number of sensitivity experiments, and Z, LWC, and ψ are calculated based on the cloud droplet spectrum output by the model. Second, the calculated Z and LWC are used to establish the Z-LWC functional relationship. Finally, the parameter b in the Z-LWC functional relationship is combined with the calculated ψ to establish the functional relationship between the parameters b and ψ (i.e., the b-ψ relationship).

[0078] (2) Establish the Z-LWC function relationship based on remote sensing observations and obtain the parameter b value in the function relationship: First, obtain Z based on the base data output by the cloud radar; second, obtain LWC based on the water content inversion method of the cloud radar; finally, combine the obtained Z and LWC to establish the Z-LWC function relationship based on remote sensing observations and obtain the parameter b value in the remote sensing observations.

[0079] (3) Calculating the uniformity of the entrainment and mixing process: Substituting the parameter b value based on remote sensing observation in step (2) into the b-ψ function relationship in step (1) as the independent variable, directly calculating ψ, and obtaining the uniformity of the entrainment and mixing process, thereby realizing the use of remote sensing to study the entrainment and mixing mechanism.

[0080] In order to make the purpose, technical solutions and advantages of the present invention more clear, Figure 2 , the present invention is described in further detail.

[0081] Step 1: Establish the functional relationship between parameters b and ψ in the Z-LWC functional relationship based on the high-resolution numerical model (i.e., b-ψ relationship).

[0082] In order to establish the relationship between the parameters b and ψ in the Z-LWC relationship, the present invention uses a high-resolution entrainment mixing model (EMPM) to simulate the entrainment mixing process in the cloud. This model is specially developed by Krueger et al. to study the entrainment mixing process. Its resolution is about 1 mm. Figure 3 A schematic diagram of the high-resolution entrainment mixing model is given in . In this model, the cloud first rises adiabatically and stops rising after reaching the entrainment height. At the entrainment height, ambient air enters the cloud through entrainment and an isobaric mixing process occurs. A portion of the cloud at a random position in the cloud is replaced by the same size of entrained ambient air and is entrained out. Under the action of the finite rate turbulent dissipation rate, the entrained unsaturated ambient air can undergo turbulent deformation, break into ambient air blocks of different sizes, and randomly distribute in the cloud. Cloud droplets can grow or evaporate accordingly according to the changes in the surrounding supersaturation.

[0083] First, the meteorological element sounding observation data-driven model was input into EMPM. By setting different factors affecting the entrainment and mixing process (initial cloud droplet number concentration, proportion of entrained ambient air, turbulent kinetic energy dissipation rate, and height of the entrainment process), a total of more than 23,000 entrainment and mixing cases were simulated. Among them, 12,218 clouds did not completely dissipate (water content greater than 0.001 gm) after the entrainment and mixing process. -3 And the cloud droplet concentration is greater than 10cm -3 ) cases to establish the b-ψ function relationship. In order to make the simulation results have better statistics, different random seeds were used for each of the 12218 cases, and the cycle was repeated 10 times. The parameter settings in EMPM are shown in Table 1.

[0084] Table 1 Parameter settings in the entrainment and mixing mode

[0085]

[0086] Secondly, according to the cloud droplet spectrum output by the entrainment mixing mode, the radar reflectivity factor is calculated using the following formula:

[0087] Z = ∫ N (D) D 6 dD (1)

[0088] Where Z is the radar reflectivity factor, D is the diameter of the droplet, and N(D) is the concentration of cloud droplets in the unit D interval.

[0089] Then, the water content LWC and cloud droplet number concentration n are calculated again based on the cloud droplet spectrum output by the entrainment mixing mode. c , volume mean radius r v The cloud microphysical quantities are as follows. Using the following Z-LWC function form, the value of the parameter b in the function form is obtained:

[0090] Z = a*LWC b (2)

[0091] Among them, parameters a and b are constants. The instantaneous Z and LWC values ​​of each case in the process of entrainment and mixing were fitted using the Z-LWC function form, and the parameter b of 12218 entrainment and mixing cases was obtained.

[0092] Again, based on the cloud microphysical quantities of the entrainment and mixing cases, ψ for 12218 cases is calculated:

[0093]

[0094]

[0095] Among them, n a 、r va , LWC a are the cloud droplet number concentration, volume mean radius and water content in the adiabatic cloud, respectively. n0 and LWC0 are the cloud droplet number concentration and water content before evaporation after entrainment, respectively, and n0 can also be considered as the number concentration under the uniform mixing mechanism; n i is the number concentration under the extremely inhomogeneous mixing mechanism, n c is the number concentration during the entrainment mixing process, r vh is the volume average radius after uniform mixing, ρ w is the density of water, LWC f It is the water content of the cloud when it reaches a new equilibrium state during the mixing and evaporation process;

[0096] Finally, the parameters b and ψ of the 12218 entrainment mixing cases were combined to establish the functional relationship between the parameters b and ψ (i.e., the b-ψ relationship), as shown in the attached figure. Figure 4 As shown:

[0097] ψ=1.11*[1-exp(-2.71*(b-1))] (4)

[0098] There are a total of 12,218 cases in this figure, and each case is cycled 10 times using different random seeds. The contours represent the joint probability density function (PDF) of ψ and parameter b. The black points and error bars represent the mean and standard deviation of ψ in each parameter b file, respectively. The mean values ​​are fitted using the weighted least squares method, where the number of data points in each parameter b file is used as the weight, and the fitting equation and the coefficient of determination R are given. 2 and p-value.

[0099] Step 2: According to the output base data of cloud radar and the water content inversion results, the Z-LWC relationship based on remote sensing observations is established and the parameter b value is obtained.

[0100] The base data directly output by the cloud radar include radar reflectivity factor, radial velocity and spectral width of velocity. Therefore, firstly, the radar reflectivity factor can be directly obtained based on the base data directly output by the cloud radar; secondly, the water content in the cloud can be obtained based on the method of inverting water content by cloud radar. For single-polarization cloud radar, the parameter adaptive method proposed by Ge et al. 2023 based on the mass absorption characteristics of single-wavelength radar can be used to invert the water content:

[0101]

[0102]

[0103] Among them, r0 is the distance from the radar to the cloud bottom, r i is the i-th distance from the cloud base, r T is the distance to the cloud top, K is the mass absorption coefficient, b is the parameter b in the Z-LWC function relationship, Z m is the reflectivity factor of radar observation, and LWP is the cloud water path.

[0104] For dual-polarization cloud radar, the water content can be inverted using the difference of dual-wavelength radar reflectivity factors (DFR) based on Socuellamos et al. 2024:

[0105]

[0106] DFR = dBZ f1 -dBZ f2 (6b)

[0107] Among them, A l , A gare the absorption coefficients of liquid water and gas, r is the distance, dBZ is the radar echo intensity, f1 and f2 are the frequencies of the dual-wavelength radar. Finally, the Z-LWC function form is used to fit the data and obtain the value of the parameter b in the function form.

[0108] Step 3: Use the b-ψ function relationship in formula (4) to quantitatively calculate the degree of uniform mixing in the entrainment mixing process.

[0109] The parameter b obtained in step 2 using remote sensing observation data is substituted as the independent variable into the b-ψ function relationship in step 1 (i.e., Formula 4) to quantitatively calculate ψ, thereby realizing the quantitative calculation of the uniform mixing degree of the cloud entrainment mixing process using remote sensing observation data.

Claims

1. A method for calculating the uniformity of cloud entrainment and mixing process based on remote sensing means, comprising the following steps: Step 1, establish the functional relationship between parameters b and ψ in the Z-LWC functional relationship based on the high-resolution numerical model; Step 2: According to the radar reflectivity factor output by the cloud radar and the inverted water content, the Z-LWC relationship based on remote sensing observations is established, and the value of parameter b is obtained; Step three, based on the value of parameter b obtained from remote sensing observations and the functional relationship between parameter b and ψ obtained from the numerical model, the degree of uniform mixing in the entrainment mixing process is calculated.

2. The method for calculating the uniformity of cloud entrainment and mixing process based on remote sensing means according to claim 1, characterized in that: The establishment of the functional relationship between the parameters b and ψ in the Z-LWC functional relationship based on the high-resolution numerical model includes: The high-resolution entrainment and mixing model is driven by the meteorological element sounding observation data, and the entrainment and mixing cases are simulated by setting different factors affecting the entrainment and mixing process. The b-ψ function relationship is established for the entrainment and mixing cases where the clouds do not completely dissipate after the entrainment and mixing process. The factors affecting the entrainment and mixing process include the initial cloud droplet concentration, the proportion of ambient air involved, the turbulent kinetic energy dissipation rate and the height at which the entrainment process occurs; the criterion for determining whether the cloud has not completely dissipated is that the water content is greater than 0.001 gm -3 And the cloud droplet concentration is greater than 10cm -3 ; The ψ is the degree of uniform mixing.

3. The method for calculating the uniformity of cloud entrainment and mixing process based on remote sensing means according to claim 2 is characterized in that: The b-ψ function relationship is established for the entrainment mixing case where the cloud does not completely dissipate after the entrainment mixing process, including: According to the cloud droplet spectrum output by the entrainment mixing model, the radar reflectivity factor is calculated using the following formula: Z=fN(D)D 6 dD Where Z is the radar reflectivity factor, D is the diameter of the droplet, and N(D) is the concentration of cloud droplets in the unit D interval; cloud microphysical quantities are calculated based on the cloud droplet spectrum output by the entrainment mixing mode. The cloud microphysical quantities include water content LWC, cloud droplet number concentration n c , volume mean radius r v ; According to the Z-LWC function form, the value of parameter b in the function form is obtained: Z=a*LUCK b Among them, parameters a and b are constants; the instantaneous Z and LWC values ​​of each case in the process of entrainment and mixing are fitted using the Z-LWC function form to obtain the parameter b of the entrainment and mixing case; According to the cloud microphysical quantities of the entrainment mixing case, ψ is obtained: Among them, n a 、r va , LWC a are the cloud droplet number concentration, volume mean radius and water content in the adiabatic cloud, respectively. n0 and LWC0 are the cloud droplet number concentration and water content before evaporation after entrainment, respectively, and n0 can also be considered as the number concentration under the uniform mixing mechanism; n i is the number concentration under the extremely inhomogeneous mixing mechanism, n c is the number concentration during the entrainment mixing process, r vh is the volume average radius after uniform mixing, ρ w is the density of water, LWC f It is the water content of the cloud when it reaches a new equilibrium state during the mixing and evaporation process; According to the combination of parameters b and ψ of the entrainment mixing case, the functional relationship between parameters b and ψ is established: ψ=1.11*[1-exp(-2.71*((b-1))].

4. The method for calculating the uniformity of cloud entrainment and mixing process based on remote sensing means according to claim 1 is characterized in that: The above-mentioned method of establishing a Z-LWC relationship based on remote sensing observations according to the radar reflectivity factor output by the cloud radar and the inverted water content to obtain the value of the parameter b includes: The radar reflectivity factor is obtained based on the basic data output by the cloud radar; the water content in the cloud is obtained based on the method of inverting water content by the cloud radar; If the cloud radar is a single polarization cloud radar, the water content is: Among them, r0 is the distance from the radar to the cloud bottom, r i is the i-th distance from the cloud base, r T is the distance to the cloud top, K is the mass absorption coefficient, b is the parameter b in the Z-LWC function relationship, Z m is the reflectivity factor of radar observation, LWP is the cloud water path; If the cloud radar is a dual polarization cloud radar, the water content is: DFR=dBZ f1 -dBZ f2 Among them, A l , A g are the absorption coefficients of liquid water and gas respectively, r is the distance, dBZ is the radar echo intensity, f1 and f2 are the frequencies of the dual-wavelength radar respectively.

5. The method for calculating the uniformity of cloud entrainment and mixing process based on remote sensing means according to claim 1, characterized in that: The value of the parameter b obtained from remote sensing observations is combined with the functional relationship between the parameter b and ψ obtained from the numerical model to obtain the uniform mixing degree of the entrainment mixing process, including: The parameter b obtained from remote sensing observation data is used as the independent variable and substituted into the b-ψ function relationship to quantitatively calculate ψ, thereby obtaining the uniform mixing degree of the cloud entrainment mixing process based on remote sensing observation data.

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