Early warning method of extreme climate and composite extreme climate comprehensive early warning system

Abstract

The invention discloses an early warning method of an extreme climate and composite extreme climate comprehensive early warning system, and belongs to the technical field of climate prediction. The system comprises a data preprocessing system, a global climate model optimization system, a regional climate model dynamic downscaling and parameterization scheme optimization system, a statistical downscaling system, a set prediction system, an extreme climate index and composite extreme climate index system, a relationship establishment system and a classification system. Future climate change scenes as many as possible are obtained through global climate model optimization, RCM regional climate model dynamic downscaling and parameterization scheme optimization in combination with a coupling dynamic-statistical downscaling mode and a set prediction mode; by calculating extreme climate indexes and composite extreme climate indexes under different scenes, the relationship between the indexes and agricultural activities is established based on a multivariate statistical method or a correlation analysis method. According to the invention, favorable support is provided for agriculture to cope with future extreme and composite extreme climate changes.

Description

technical field [0001] The invention relates to the technical field of climate prediction, in particular to an early warning method for an integrated early warning system for extreme weather and compound extreme weather. Background technique [0002] Under the circumstances of the current abnormal climate, especially when there is no prepared response plan, nature, society, and human activities are extremely vulnerable to extreme weather. And many places have never experienced extreme climate and compound extreme climate. In addition, climate extremes and combined extremes have a huge impact on various parts of the world, especially in agriculture. [0003] At present, research in this area mainly involves the following issues and challenges: (1) Most of the adaptive research on the optimization of regional climate model parameterization schemes only focuses on one or two individual parameterization schemes, and rarely considers the relationship between different parameteri...

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Problems solved by technology

[0003] At present, research in this area mainly involves the following issues and challenges: (1) Most of the adaptive research on the optimization of regional climate model parameterization schemes only focuses on one or two individual parameterization schemes, and rarely considers the relationship between different parameterization schemes. (2) Due to the influence of different climate models and different downscaling methods, there are uncertainties in the simulation and prediction of future climate, which will lead to inaccurate calculation results of extreme climate indicators and composite extreme climate indicators, and further contribute to agricultural protection. Policy formulation and facility construction bring hidden dangers; (3) similar early warning systems generally predict a single extreme climate indicator, and it is difficult to consider multiple extreme climate indicators at the same time, let alone the simulation and prediction of compound extreme climates; (4) Current early warning systems do not establish relationships between climate extremes and composite extremes and agricultural activities through multivariate analysis

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