Seasonal climate statistical prediction method, system and device and storage medium

Abstract

The invention discloses a seasonal climate statistical prediction method, which is used for solving the problems of poor pertinence of feature factors and model optimization, simple feature information and regression algorithm, poor spatial distribution prediction skill of climate abnormality and the like in the existing climate statistical prediction method. The method comprises the following steps: acquiring meteorological data within a specified duration; preprocessing the meteorological data to obtain forecast object data, and performing principal component decomposition on the forecast object data to obtain at least one forecast quantity; obtaining monthly specified variable data of global grid points, and carrying out time dimension average and differential preprocessing on the specified variable data to obtain a plurality of global range feature information fields; respectively calculating a correlation coefficient between each forecast quantity and each global range feature information field by adopting a one-leaving method, and establishing a forecast factor according to the position of the maximum value of the correlation coefficient; and performing statistical modeling on the forecasting factors by using a distributed gradient enhancement algorithm to obtain a climate forecasting model, and forecasting the climate of the year to be forecasted.

Description

technical field [0001] The present application relates to the field of meteorological forecasting, in particular to a method, system, device and storage medium for seasonal climate statistical forecasting. Background technique [0002] At present, we rely on two aspects for short-term climate prediction: one is to establish computerized climate models and data assimilation systems based on various observational data and climate system equations and use them for prediction; Station observation data and atmospheric-ocean circulation data are used to establish forecasting factors and statistical models based on empirical methods and forecast the future. [0003] However, current statistical methods and climate model predictions are generally poor at predicting the spatial distribution of climate anomalies. Existing statistical methods are usually optimized for historical periods in predictor production and model training, rather than specific processing of the years to be pred...

AI Technical Summary

Problems solved by technology

[0005] The embodiment of this application provides a seasonal climate statistical forecasting method to solve the existing statistical climate forecasting methods, there are characteristic factors and model optimization are not targeted, the characteristic information and regression algorithm are simple, and the spatial distribution prediction skills of climate anomalies are poor And other issues

[0006] The embodiment of the present application also provides a seasonal climate statistical forecasting system, which is used to solve the existing statistical climate forecasting methods, which have characteristic factors and model optimization that are not well targeted, feature information and regression algorithms are simple, and spatial distribution prediction skills of climate anomalies Poor and other issues

Images