Inter-year forecast initialization method and system

Abstract

The invention provides an inter-year forecast initialization method and system, which relate to the technical field of inter-year climate prediction. The method comprises the steps that a forecast initial field is obtained based on historical simulation of a global coupling mode, and multiple sets of atmosphere forecast initial fields are obtained; based on ocean and sea ice historical simulation driven by atmosphere reanalysis data, the climate state of the ocean and sea ice historical simulation is corrected to be the climate state of ocean and sea ice of global coupling mode historical simulation, and an ocean and sea ice forecast initial field is obtained; the obtained multiple sets of atmosphere forecast initial fields are combined with land, ocean and sea ice initial fields to construct multiple sets of initial fields of inter-year ensemble forecast; a pre-constructed inter-year forecast system is initialized, and historical post-reporting or inter-year forecast of a future business type set is implemented. According to the method, the business type inter-year prediction can be ensured, the influence caused by impact after initialization is reduced, the accuracy of natural change rate prediction of the prediction system is improved, and thus the business prediction level of the inter-year prediction system is enhanced.

Description

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AI Technical Summary

Benefits of technology

This invention relates to an improved method that combines atmospheric monitoring from different sources into one framework to predict changes over time during weather conditions on Earth (atmosphere). It improves upon existing methods by combining multiple fields together based on their respective characteristics such as altitude, latitude, water temperature, etc., which can be used alone without affecting other factors like precipitation levels at specific locations along its trajectory. By doing this, it provides more accurate predictions about changing environmental variables than current models.

Problems solved by technology

This patented describes methods for accurately estimating long term temperature changes from seawater data collected over different periods during an ice sheet's melting cycle (the phase when water starts evaporation). These techniques involve identifying specific variables that drive these processes, calculating their effects or correlates them through various mathematical relationships like regression coefficients, autoconvergence functions, etc., which help make accurate future weather predictions more efficient than current approaches involving longer physical measurements alone.

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