Sea fog level intelligent forecasting method and system

A forecasting system and intelligent technology, applied in marine science and atmospheric fields, can solve problems such as the inability to accurately reflect multi-variable interactions in the atmospheric and oceanic fields, and achieve the effect of improving forecasting skills at low visibility levels

Pending Publication Date: 2022-04-05
无锡九方科技有限公司
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  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

[0004] At present, feature selection methods in machine learning are generally based on bivariate correlation analysis, which cannot accurately reflect the complex interactions between multiple variables in the atmosphere and ocean fields.

Method used

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  • Sea fog level intelligent forecasting method and system
  • Sea fog level intelligent forecasting method and system
  • Sea fog level intelligent forecasting method and system

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Experimental program
Comparison scheme
Effect test

Embodiment 1

[0062] refer to Figure 1-10 , a sea fog level intelligent forecasting system and method, comprising the following steps:

[0063] S1. Collection of numerical model forecast results and routine observation data of meteorological stations, as well as fusion and quality control of collected data;

[0064] S101. Prepare the routine observation data A1 of meteorological stations from 2016 to 2020. The elements include: sea level pressure, wind speed, air temperature, dew point, visibility, 1-hour precipitation, 3-hour precipitation, 6-hour precipitation, and 24-hour precipitation ;

[0065] S102. Prepare the numerical model forecast data A2 from 2016 to 2020. The elements are divided into ground field and high-altitude field. Ground field elements include: sea level pressure, variable pressure, temperature, humidity, wind direction and wind speed; high-altitude field elements include: 500hPa, 700hPa , 850hPa, 925hPa, 1000hPa isobaric surface potential height, temperature, dew po...

Embodiment 2

[0098] The system scheme is as figure 1 As shown, it includes five modules including data layer, feature analysis, intelligent correction, model training, and forecast inspection; the main invention point is the organic fusion of five modules to form a sea fog level intelligent forecast method and system; the first layer of data layer is responsible for The collection of numerical model forecast results and site observation data, as well as the fusion and quality control of collected data; the feature analysis layer is mainly used to extract key meteorological elements that affect visibility. Feature analysis methods include at least Pearson correlation coefficient test, causality test, Time-lag correlation analysis, etc.; the intelligent correction layer is responsible for correcting the key meteorological elements in the numerical model forecast results by using machine learning correction methods based on a large number of station observation data; the model training layer i...

Embodiment 3

[0110] Such as Figure 8-9 As shown, taking the visibility level forecast of 27 meteorological observation stations in the Yangtze River Estuary as an example, the effect of the invention is explained; among them, the model forecast is the result of visibility diagnosis by the operational operation of the WRF model, and the intelligent forecast is the result of the intelligent forecast of visibility based on the LightGBM algorithm , it can be seen through the comparison of ETS scores of different forecasting timeliness that for different forecasting timeliness, the visibility level intelligent forecasting technique of the present invention is better than the general numerical forecasting diagnosis method; Increased by more than 1.5 times.

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Abstract

The invention relates to the technical field of atmosphere and ocean science, and discloses a sea fog level intelligent forecasting method and system, which comprises the following steps: collecting a numerical mode forecasting result and conventional observation data of a meteorological station, and fusing and controlling the quality of the collected data; the method comprises the following steps: extracting key meteorological elements influencing visibility as forecasting factors by using feature analysis methods such as Pearson correlation coefficient test, causal correlation test and time lag analysis, and meanwhile, using visibility observation and geographical time factors in a period of time before mode report start as auxiliary forecasting factors; correcting key meteorological elements in a numerical mode forecasting result by adopting a machine learning correction method based on a large amount of site observation data; a sea fog intelligent forecasting model is built and optimized by adopting technologies such as a machine learning algorithm, hyper-parameter automatic tuning and integrated learning; and carrying out grade forecasting on the visibility by using the sea fog intelligent forecasting model, realizing site forecasting and grid forecasting of the visibility, and checking the forecasting accuracy.

Description

technical field [0001] The invention relates to the field of atmospheric and marine science and technology, in particular to an intelligent sea fog level forecasting method and system. Background technique [0002] Sea fog is a condensation phenomenon that occurs in the lower atmosphere of the sea or coastal areas under the influence of the ocean. It is a weather phenomenon in which a large number of water droplets or ice crystals suspended in the atmospheric boundary layer make the horizontal visibility of the atmosphere less than 1km. With the development of society and economy, sea, road and air traffic are becoming more and more busy, and the low visibility caused by frequent occurrence of sea fog directly threatens the economic activities and the safety of people's life and property in coastal areas. Due to the variability and local characteristics of fog, the forecast of fog has always been one of the difficulties in weather forecasting. In business applications, fog ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01W1/10G06N20/00
Inventor 黄小猛向妍霏王明清梁逸爽周峥
Owner 无锡九方科技有限公司
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