Cross-year and long-effectiveness climate prediction method

Abstract

The invention discloses a multi-year short-term climate prediction method based on a multi-factor regression set, a cross-check set, and a month-by-month rolling set, and belongs to the field of short-term climate prediction theory and methods in meteorology. The method of the present invention includes, firstly, according to the large-scale barotropic eddy equation, using the potential function field and the flow function field reflecting the effects of the advection term and the exogenous forcing term in the theoretical equation as the predictor field; then, considering the combination of different factor time effects and Its independence, comprehensive application of multi-factor regression set, cross-check set, month-by-month rolling set, to predict the target. The invention has improvements in the selection of the basic factor field, the determination of the final factor and the application of various sets. Its advantages lie in the characteristics of long prediction timeliness, simple calculation relative model, good prediction effect, strong regional adaptability, etc., and can be applied to prediction problems of other scales and different element variables.

Description

technical field [0001] The invention belongs to the technical field of climate prediction in atmospheric science, and in particular relates to a multi-year, long-term climate prediction method. Background technique [0002] The climate system includes the atmosphere, cryosphere, hydrosphere, lithosphere and biosphere, and regional climate anomalies are affected by different factors in the above climate system. Due to the large spatial scale and long time scale of the climate system, climate anomalies and their causes are quite complex; and it is even more difficult to predict climate anomalies. Current climate prediction is not only an international research frontier and hotspot, but also a world problem yet to be solved. The climate prediction business that has been carried out in my country is mainly concentrated on the monthly, seasonal, and annual scales, that is, short-term climate prediction; especially the abnormal summer drought and flood has a great impact on the n...

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Problems solved by technology

[0004] Climate models may be the direction for the development of future forecasting methods, but the forecasting level of existing models is not high, especially in the East Asian subtropical monsoon region.

Theoretically, the numerical prediction problem is an initial value problem, and its weakness is that a large amount of historical data cannot be fully applied.

However, the model atmosphere is also similar to the observed atmosphere. The climate system variables have complex multi-scale characteristics, and the errors of climate models for some forecast elements are also unstable, and the relationship between them and related error correction factors is also time-varying. It has also become one of the important problems to be solved in dynamic statistical error correction

[0005] Due to the fact that the timeliness of current model predictions is not long enough, the time-varying nature of dynamic statistical methods, and the complexity of predictors, the actual climate prediction business is still based on the analysis of forecasters and is made with reference to model numerical forecasts, resulting in low work efficiency for forecasters. The accuracy of the results is also unstable

Moreover, after the actual climate anomaly occurs, it is not easy to find a quantitative objective basis for retrospective inspection and cause diagnosis compared with the forecast, and the diagnosis is cumbersome.

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