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Deep learning-based downscaling processing method and system for aviation meteorological data

A meteorological data and deep learning technology, applied in data processing applications, neural learning methods, climate sustainability, etc., can solve problems such as early warning and prompting of precipitation in the airport area, and achieve the effect of avoiding aviation accidents and improving safety

Active Publication Date: 2022-08-09
TAIJI COMP +1
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  • Claims
  • Application Information

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Problems solved by technology

[0004] In view of this, the present invention proposes a method and system for downscaling processing of aviation meteorological data based on deep learning, aiming to solve the problem of how to carry out precipitation warning and reminder for the airport area

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  • Deep learning-based downscaling processing method and system for aviation meteorological data
  • Deep learning-based downscaling processing method and system for aviation meteorological data

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[0065] Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that the present disclosure will be more thoroughly understood, and will fully convey the scope of the present disclosure to those skilled in the art. It should be noted that the embodiments of the present invention and the features of the embodiments may be combined with each other under the condition of no conflict. The present invention will be described in detail below with reference to the accompanying drawings and in conjunction with the embodiments.

[0066] In the embodiment of the present invention, the data sources use the national meteorological bureau radar data...

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Abstract

The invention provides a downscaling processing method and system for aviation meteorological data based on deep learning. The downscaling processing method comprises the steps that historical rainfall information of a to-be-monitored area is acquired; carrying out downscaling processing on the meteorological information of the to-be-monitored area based on the global climate mode; determining a historical rainfall grade; determining a predicted precipitation time period and a predicted precipitation amount in the predicted precipitation data, and comparing the predicted precipitation time period with a historical precipitation time period to determine a predicted precipitation level of the predicted precipitation time period; and outputting prompt information according to the determined predicted rainfall grade. The historical rainfall information and the predicted rainfall information in the airport area range are fused, the predicted rainfall information can be adjusted and corrected by referring to the historical rainfall data, and the objective and accurate predicted rainfall level is obtained, so that rainfall early warning and prompting of the airport area can be performed according to the predicted rainfall level, and the accuracy of rainfall early warning is improved. The prediction rainfall information of the airport area can be effectively obtained, and rainfall early warning prompt can be timely and effectively carried out.

Description

technical field [0001] The present invention relates to the technical field of meteorological data processing, in particular, to a method and system for downscaling processing of aviation meteorological data based on deep learning. Background technique [0002] At present, the forecast of severe convective weather in the field of aviation meteorology mainly relies on the subjective judgment of forecasters, and there is no effective objective forecasting method and tool. Short-term nowcasting is widely used in business, mainly using the linear extrapolation method, that is, based on Doppler radar echo characteristics, combined with ground encrypted observations (precipitation and wind field), satellite cloud images, lightning location information and strong convection live etc., mainly based on the subjective analysis and forecast of forecasters, to judge and extrapolate the satellite cloud image and radar echo intensity. [0003] In the prior art, there is no effective earl...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04G06K9/62G06N3/04G06N3/08
CPCG06Q10/04G06N3/08G06N3/045G06F18/241Y02A90/10
Inventor 彭渊郭培贤孙永亮付文杰李奕飞鲁定一董锦芝王孟宇
Owner TAIJI COMP
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