Short-impending rainfall prediction method based on ConvLSTM and 3D-CNN

Abstract

The invention discloses a short-impending rainfall prediction method based on ConvLSTM and 3D-CNN, and belongs to the technical field of weather forecast. The method comprises the following steps: firstly, inputting a historical radar echo map, a gridding temperature and total rainfall at a moment t, and performing data cleaning and denoising on the historical radar echo map and the gridding temperature; performing statistical analysis on the rainfall data imbalance problem, and establishing a new loss function using different weights at different rainfall rate levels; secondly, standardizingthe gridding temperature and the total rainfall by using a meteorological data mapping method based on power and logarithm transformation; and finally, fusing the t-moment input data subjected to theprevious step into a data block, carrying out model building and testing based on a convolutional long-term and short-term memory neural network and a three-dimensional convolutional neural network, and outputting a short-term and temporary rainfall prediction result. According to the method, the rainstorm prediction precision can be improved, the meteorological data is reasonably visualized and standardized, the image features of various meteorological data are fused, and the noise interference is reduced.

Description

technical field [0001] The invention belongs to the technical field of weather forecasting, in particular to a short-imminent precipitation forecasting method based on ConvLSTM and 3D-CNN. Background technique [0002] Changes in meteorological factors (such as wind speed, temperature, humidity, precipitation, etc.) have profoundly affected human life. Accurate forecasting of future meteorological elements can be widely used in people's daily life, transportation, agriculture, forestry and animal husbandry, disaster-causing weather and other fields. As the number of Earth-observing satellites grows and climate models become more sophisticated, weather researchers are faced with ever-larger volumes of data. [0003] At present, numerical forecasting and artificial intelligence forecasting based on numerical forecasting data are the main methods of weather forecasting. For numerical weather prediction methods, short-term forecasts require complex physical atmospheric model s...

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Problems solved by technology

[0005] Purpose of the invention: The purpose of the present invention is to provide a short-imminent precipitation prediction method based on ConvLSTM and 3D-CNN, which is not only beneficial to the training of the model and improves the prediction accuracy of short-imminent precipitation, especially the prediction accuracy of heavy rain, but also can solve the problems existing in the prior art. Unbalanced precipitation data, low rainstorm prediction accuracy, inappropriate strategies for meteorological data visualization and standardization, and few technical problems in model fusion

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