Forecast of the trend of heavy fog based on the VARIMAX model

This paper works out relationship between visibility and near-surface meteorological factors. The formation of heavy fog is affected by meteorological factors near the ground and fog in the past period. In this paper, we abstract and simplify the problem as a time series problem. First, the airport...

Full description

Bibliographic Details
Main Authors: Peng Boyang, Meng Yuchi, Shi Dapai, Dai Mingyu, Zhou Hao, Chen Tingxuan
Format: Article
Language:English
Published: EDP Sciences 2021-01-01
Series:E3S Web of Conferences
Online Access:https://www.e3s-conferences.org/articles/e3sconf/pdf/2021/33/e3sconf_aesee2021_03013.pdf
Description
Summary:This paper works out relationship between visibility and near-surface meteorological factors. The formation of heavy fog is affected by meteorological factors near the ground and fog in the past period. In this paper, we abstract and simplify the problem as a time series problem. First, the airport AWOS observation data is reprocessed, and some missing and incorrect data are supplemented and corrected. Then draw a distribution map of “Visibility-Near-surface Meteorological Factors” to intuitively grasp the correlation between them. Finally, model the classic VARIMAX to fit the mapping relationship between visibility and near-surface meteorological factors. The results show temperature has the greatest impact on visibility index, positively correlated with it; secondly, dew point temperature index negatively correlated with it. The results show that, with the temperature low and the humidity high, the water vapor in the atmosphere is more likely to condense into mist, which is not easy to dissipate, resulting in reduced visibility. The indicators related to air pressure and wind speed are positively correlated with visibility, indicating that the increase in air pressure and the increase in wind speed will promote the dissipation of heavy fog. Generally speaking, the MOR index fits better with near-surface meteorological factors.
ISSN:2267-1242