An airport cloud and fog comprehensive early warning system and method based on multi-source equipment networking

Abstract

The present invention discloses a multi-source equipment networking-based airport cloud and fog integrated early warning system and method. According to the system, an in-airport meteorological observation device sends collected in-airport meteorological data to a data processing server; an in-airport self-observation database sends airport self-observation data to the data processing server; a meteorological bureau multi-source database sends meteorological observation data to the data processing server; the data processing server sends a meteorological map generated according to received meteorological data to a control monitoring computer, compares the parameter numerical values of the received meteorological data with pre-stored meteorological early warning threshold values, generates meteorological early warnings when one or more parameter numerical values exceed the meteorological early warning threshold values, and sends the meteorological early warnings to the control monitoring computer; and the control monitoring computer displays the meteorological map and displays the meteorological early warnings on the meteorological map. With the system and method adopted, real-time monitoring on and early warning against heavy fog and low cloud in the surrounding environment of an airport can be well realized.

Description

technical field [0001] The invention relates to the field of airport cloud and fog comprehensive early warning, in particular to an airport cloud and fog comprehensive early warning system and method based on multi-source equipment networking. Background technique [0002] In airport meteorological support, heavy fog and low clouds have a major impact on airport flight operations. In the original airport cloud and fog early warning system, forecasters need to make artificial judgments based on instrument data such as visibility meters, human eye observations, and laser ceilometers, which cannot accurately and effectively judge early warnings; The humidity field cannot effectively give the prediction of dissipation and the early warning of low cloud and heavy fog. At the same time, the visibility meter, human eye observation, and laser ceilometer are all limited under different working conditions, and cannot provide accurate data information in real time. Contents of the i...

AI Technical Summary

Problems solved by technology

In the original airport cloud and fog early warning system, forecasters need to make artificial judgments based on instrument data such as visibility meters, human eye observations, and laser ceilometers, which cannot accurately and effectively judge early warnings; The humidity field cannot effectively give predictions of dissipation and early warning of low cloud and heavy fog

At the same time, the visibility meter, human eye observation, and laser ceilometer are limited under different working conditions, and cannot provide accurate data information in real time

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