Nanjing University of Information Science & Technology

National Climate Center

Xikun Wei

Tong Jiang

Guojie Wang

Yanjun Wang

Guofu Wang

Mingyue Lu

The present disclosure provides a meteorological big data fusion method based on deep learning, including the following steps: constructing multi-source meteorological data samples; according to an original resolution of different climate variables, selecting a corresponding super-resolution multiple to obtain an optimized super-resolution module under the constraint of maximizing information retention efficiency; constructing a spatial-temporal attention module using a focused attention mechanism, and selecting a corresponding time stride according to periodic characteristics of different climate variables; constructing a meteorological data fusion model in combination with the optimized super-resolution model and the spatial-temporal attention module; taking a minimum resolution of climate variables as a loss function, and training the meteorological data fusion model with the multi-source meteorological data samples; and importing the acquired real-time meteorological data from multiple data sources into the trained meteorological data fusion model to obtain high-resolution fused meteorological data.

Growing community of inventors

Xinghua, China

Xikun Wei