Subseasonal-seasonal-interannual scale integrated climate model ensemble prediction system

Abstract

The invention discloses a subseasonal-seasonal-interannual scale integrated climate model ensemble prediction system, including an initialization module, a high-resolution climate model module, an ensemble prediction module and a post-prediction processing module. The initialization module is used for downloading, extracting and processing the included Multi-source data of the atmosphere, land surface, ocean, and sea ice, using external parameters to control and realize data selection, inspection, horizontal and vertical interpolation of meteorological elements and other pre-processing, suitable for data pre-processing of all climate model operations, high resolution The climate model module is used to objectively and quantitatively predict the coupled and coordinated changes of the atmosphere, land surface, ocean, and sea ice. The ensemble prediction module is used to generate any number of ensembles that combine random disturbances of physical parameters and initial value time lag methods. Predict sample membership. The invention provides a multi-time-scale and multi-space-scale climate prediction of the atmosphere, land surface, ocean and sea ice with high resolution, high prediction accuracy and good maneuverability.

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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