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CN-121995549-A - Atmospheric visibility prediction method considering cloud drop concentration

CN121995549ACN 121995549 ACN121995549 ACN 121995549ACN-121995549-A

Abstract

The invention discloses an atmospheric visibility prediction method considering cloud drop concentration, which additionally considers the influence of the cloud drop concentration on visibility under different pollution conditions when constructing a physical relationship model in fog, deduces a visibility diagnosis calculation formula, and after a reasonable cloud drop concentration value is set, applies the formula to main stream numerical prediction products such as GFS, ECMWF, CMA-MESO and the like, substitutes basic weather quantity, and obtains a visibility diagnosis prediction result. The method is suitable for the visibility forecast under different pollution conditions, has high calculation speed, does not occupy extra storage, does not need a large number of sample training, has strong expansibility, and provides theoretical and technical support for the development of the fine forecast and early warning technology of fog.

Inventors

  • YAN SHUQI
  • MU XIYU
  • WU HAO
  • YANG HUADONG
  • ZENG YAN
  • WANG HONGBIN
  • LIU DUANYANG
  • LU CHUNSONG
  • ZHU SHOUPENG
  • LIU XIAOHUI
  • ZU FAN
  • ZHU JUN
  • WANG YUAN

Assignees

  • 南京气象科技创新研究院

Dates

Publication Date
20260508
Application Date
20260409

Claims (7)

  1. 1. An atmospheric visibility prediction method considering cloud drop concentration is characterized by comprising the following steps: S1, acquiring numerical mode forecast data, wherein the numerical mode forecast data comprise air pressure p, temperature T, 1000hpa height z 1000hpa and relative humidity RH; S2, constructing a time change equation of the fog concentration based on a physical rule in fog; S3, confirming the value of the cloud drop concentration N d according to the atmospheric pollution condition; S4, constructing an intermediate parameter equation to obtain values of fog water generation/consumption beta and sedimentation rate parameter a; S5, obtaining fog concentration q at different moments through a time change equation of the fog concentration based on the cloud number concentration N d and the intermediate parameters a and beta obtained in the steps S3 and S4, and obtaining a visibility value VIS.
  2. 2. The atmospheric visibility prediction method according to claim 1, wherein said time-varying equation of said fog concentration in step S2 is represented by formula (1), (1) In the formula (1), the components are as follows, The water mist concentration change rate with time, the height of the mist roof, which represents the maximum height of the relative humidity above the ground, which is continuously greater than 95%, a is the sedimentation rate parameter, and β is the mist generation/consumption rate.
  3. 3. The atmospheric visibility prediction method considering cloud cover concentration according to claim 1, wherein in step S4, by constructing intermediate parameter calculation formulas (2) and (3), mist generation/consumption beta and sedimentation rate parameter a are calculated, respectively, (2) In the formula (2), gamma 1000hpa and gamma sfc represent values of condensation rate of 1000hpa and ground, respectively, deltaT 1000hpa and DeltaT sfc represent values of temperature change at 1000hpa and ground, respectively, deltat is a time interval, z 1000hpa is a height of 1000hpa, Is a function of the rate of coagulation, Is the air temperature at the current time 1000hpa, Is the temperature at the ground at the current moment, L v represents the latent heat constant of water vapor condensation 2.5X10. 10 6 J/kg,R v represents the specific vapor constant of water vapor, the value is 461.5J/kg, p is the air pressure, T is the temperature, the air pressure p, the temperature T, 、 Z 1000hpa are all ready-made variables in the numerical forecasting product; (3) In the formula (3), Γ is a Gamma function in mathematics, ρ w is the density of water, g is the gravitational acceleration, ν is the aerodynamic viscosity coefficient, 1.72X10- -5 Pa s;N d is the cloud number concentration, and μ represents the distribution parameter of the fog drop spectrum.
  4. 4. The method of claim 1, wherein the visibility value VIS in step S5 is obtained by the following equation, vis=1002 (q×n d ) -0.6473 .
  5. 5. The method for predicting atmospheric visibility taking into consideration cloud computing as defined in claim 1, wherein when the mist water concentration q obtained in step S5 is negative, the value of the mist water concentration q is set to 0.
  6. 6. The method for predicting atmospheric visibility with consideration of cloud computing concentration as defined in claim 1, wherein said numerical modes include a global forecast system mode GFS of the national weather agency, an ECMWF of the middle weather forecast center in Europe, and a CMA-MESO of the middle-scale weather numerical forecast system mode of the Chinese weather agency.
  7. 7. The atmospheric visibility prediction method according to claim 1, wherein in step S3, when the PM2.5 pollution level is excellent, the cloud point concentration Nd is 50, when the PM2.5 pollution level is good, the cloud point concentration Nd is 100, when the PM2.5 pollution level is lightly polluted, the cloud point concentration Nd is 250, and when the PM2.5 pollution level is moderately or severely polluted, the cloud point concentration Nd is 500.

Description

Atmospheric visibility prediction method considering cloud drop concentration Technical Field The invention belongs to the technical field of atmospheric weather prediction, and particularly relates to an atmospheric visibility prediction method. Background Mist is a typical low visibility weather phenomenon that forms suddenly and develops rapidly, with a great adverse effect on transportation. With the perfection of atmospheric science theory and the development of computer technology, numerical modes are widely applied to simulation and prediction of fog. There is usually no output result of fog and visibility in the current business numerical forecasting mode, and the visibility needs to be calculated by a statistical method or an artificial intelligence method. A statistical or artificial intelligent model is established, a large amount of historical observation and forecast product data is needed to be used as training samples to obtain accurate visibility calculation results, so that a large amount of calculation power resources and storage resources are consumed, and satisfactory results cannot be obtained after one training. When the existing statistical or artificial intelligent model is applied to another numerical model product, retraining is also needed, and the research and development period of the numerical product fog forecasting technology is remarkably increased. The existing numerical forecasting product can obtain a visibility forecasting result without depending on historical data, but the traditional numerical mode forecasting product only considers the fog concentration when carrying out visibility forecasting, and does not consider the influence of the cloud drop concentration under the pollution condition. By combining with the weather theory, the cloud drop concentration can reduce the sedimentation rate of the fog drops under the pollution condition, and the fog water concentration is increased to further reduce the visibility, so that the cloud drop concentration plays an important role in the visibility prediction. The existing forecasting technology does not contain the effect and cannot be suitable for the visibility forecasting of different pollution situations. To take this effect into account, it is necessary to correct and re-solve the atmospheric law equation of the fog, which is not obvious and currently no reference is made. Disclosure of Invention Aiming at the problems and the defects existing in the prior art, the invention provides an atmospheric visibility prediction method considering cloud droplet concentration, which additionally considers the influence of the cloud droplet concentration on visibility under different pollution conditions when constructing a physical relation model in fog, deduces a visibility diagnosis calculation formula, and applies the formula to a GFS, ECMWF, CMA-MESO and other main stream numerical prediction products after setting a reasonable cloud droplet concentration value, substitutes basic meteorological quantity, and obtains a visibility diagnosis prediction result. The method is suitable for the visibility forecast under different pollution conditions, has high calculation speed, does not occupy extra storage, does not need a large number of sample training, has strong expansibility, and provides theoretical and technical support for the development of the fine forecast and early warning technology of fog. The technical scheme is that the atmospheric visibility prediction method considering cloud drop concentration comprises the following steps of: S1, acquiring numerical mode forecast data, wherein the numerical mode forecast data comprise air pressure p, temperature T, 1000hpa height z 1000hpa and relative humidity RH; S2, constructing a time change equation of the fog concentration based on a physical rule in fog; S3, confirming the value of the cloud drop concentration N d according to the atmospheric pollution condition; S4, constructing an intermediate parameter equation to obtain values of fog water generation/consumption beta and sedimentation rate parameter a; S5, obtaining fog concentration q at different moments through a time change equation of the fog concentration based on the cloud number concentration N d and the intermediate parameters a and beta obtained in the steps S3 and S4, and obtaining a visibility value VIS. Further, the time change equation of the fog concentration in the step S2 is shown as a formula (1), (1) In the formula (1), the components are as follows,The water mist concentration change rate with time, the height of the mist roof, which represents the maximum height of the relative humidity above the ground, which is continuously greater than 95%, a is the sedimentation rate parameter, and β is the mist generation/consumption rate. Further, in step S4, by constructing intermediate parameter calculation formulas (2) and (3), the mist generation/consumption beta and the sedimentation rate parameter