Method for detecting climatic mode index sequence mutation point, storage medium and equipment

Abstract

The invention relates to a method, a storage medium and equipment for detecting a climatic mode index sequence mutation point. And reading observation sequence data, determining cut-off lengths and probability levels of climate modes, and calculating statistically significant difference values among different modes. And starting to cyclically search a sudden change point, if the value of a certain point is remarkably different from that of the previous climate mode, considering the point as a candidate point of climate mode sudden change, otherwise, moving to the next point. And after the candidate point is determined, calculating the mode conversion index of the point, if the index has a negative value, indicating that the mode mutation fails, and if the index has a positive value, indicating that the mutation succeeds, and formally determining the point as a mode mutation point. And taking the new mode as a reference mode, continuing the operation until the end of the observation sequence, and detecting all mode mutation points. The method solves the problem that the detection performance of the existing method is sharply reduced at the tail end of the sequence, and the climate mode transfer can be detected as early as possible and then the change of the amplitude along with time is monitored. The method is easy to operate, and a user can change input parameters according to requirements.

Description

technical field [0001] The invention relates to a method for detecting the sudden change point of the climate model index sequence, in particular to a process algorithm for calculating and identifying the sudden change point of the climate model. Background technique [0002] Changes in different phases of climate models are of great value to the study of climate change. Methods for detecting abrupt changes in existing climate models typically use confirmatory statistical techniques and a priori assumptions about the timing of changes. Although there are methods to automatically detect discontinuities in time series, the performance of existing methods drops off sharply at the end of the series due to the necessity to accumulate enough data (at least 10 years or more) to apply a formal statistical test . Furthermore, the climate system may be about to switch to the opposite state again when enough data becomes available. Contents of the invention [0003] Aiming at the ...

AI Technical Summary

Problems solved by technology

Although there are methods to automatically detect discontinuities in time series, the performance of existing methods drops off sharply at the end of the series due to the necessity to accumulate enough data (at least 10 years or more) to apply a formal statistical test

Furthermore, the climate system may be about to switch to the opposite state again when sufficient data become available

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