Sub-season-season-interannual scale integrated climate mode set prediction system

Abstract

The invention discloses a sub-season-season-interannual scale integrated climate mode set prediction system. The system comprises an initialization module, a high-resolution climate mode module, a set prediction module and a prediction post-processing module. The initialization module is used for downloading, extracting and processing multi-source data including atmosphere, land surface, ocean and sea ice, and using external parameters for controlling and achieving preprocessing such as data selection, checking and horizontal and vertical interpolation of meteorological elements, and the initialization module is suitable for data preprocessing of operation in all climate modes. The high-resolution climate mode module is used for carrying out objective quantitative prediction on multi-circle coupling collaborative change of atmosphere, land surface, ocean and sea ice; the set prediction module is used for generating any number of set prediction sample members combined by physical parameter tendency random disturbance and an initial value time lag method. The invention provides the climate prediction with high resolution, high prediction accuracy and good controllability, and provides multi-time-scale and multi-space-scale climate prediction of atmosphere, land surface, ocean and sea ice.

Description

technical field [0001] The invention relates to the technical field of climate prediction, specifically a subseasonal-seasonal-interannual scale integrated climate model ensemble prediction system. Background technique [0002] The problem of climate prediction is a worldwide problem. It is not only a frontier topic of international climate change research, but also an urgent need for national disaster prevention and reduction and climate change response. Climate model is the most objective tool and method for climate prediction. Therefore, the research and development of climate model system and ensemble prediction technology based on climate model are the current research focus of meteorological circles around the world. In the past, weather and climate predictions for weather scales and extended periods were based on separate atmospheric models, while seasonal and interdecadal climate predictions were based on coupled climate models. Therefore, climate predictions for dif...

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Problems solved by technology

In the past, weather and climate predictions for weather scales and extended periods were based on separate atmospheric models, while seasonal and interdecadal climate predictions were based on coupled climate models. Therefore, climate predictions for different time scales required running several sets of prediction subsystems separately, which cost a lot of money. A large number of computer resources and storage resources cannot meet the needs of forecasting business and social services

In the process of climate model prediction, not only the initial value of the atmosphere is very important, but also the initial value information of elements such as ocean, land surface, and sea ice. The initial disturbance scheme and ensemble prediction scheme of the model have different effects on climate prediction at different time scales. The initial perturbation schemes of previous climate prediction models used methods such as the initial value time-lag method of the atmosphere or sea surface temperature, the singular vector method, and physical parameter perturbation methods to construct ensemble sample members. This single initial value perturbation method improves the prediction performance have greater limitations

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