Abnormal relative tendency generation method and system for climate prediction

A climate and tendency technology, applied in the field of digital signal processing and climate prediction, can solve the problems of inconsistency in magnitude and phase, lack of universality and universality, initial value error, etc., and achieve the effect of ensuring consistency

Pending Publication Date: 2022-04-12
NANJING UNIV
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Problems solved by technology

[0007] Purpose of the invention: Aiming at the problem that existing commonly used filtering methods in climate research cannot be applied at the end of the time series, and the existing solutions to the end problem may introduce initial value errors into climate predictions, may cause inconsistencies in magnitude and phase, lack of universal properties and general To solve the problem of adaptability, the present invention provides a method and system for generating relative tendency of anomalies for c

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  • Abnormal relative tendency generation method and system for climate prediction
  • Abnormal relative tendency generation method and system for climate prediction
  • Abnormal relative tendency generation method and system for climate prediction

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[0046] The invention is further described below with reference to the accompanying drawings and the specific embodiments, which are intended to illustrate the invention and is not limited to the scope of the invention. After reading the present invention, the modifications of various equivalents of the present invention have fallen in the scope of the claims appended claims.

[0047] Such as figure 1 As shown, an abnormality of the present invention is used for the abnormality relative tendency to generate the climate prediction comprises the following four modules, and the original data input system passes through each module, which can generate an abnormally relative tendency and output:

[0048] (1) Time Smooth Module: Get raw data, smooth the original data, remove high frequency variable rate.

[0049] For example, when the original data is a daily average daily value of a climate variable, the prediction target is the climate averaging in the future seasonal scale, and it is ...

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Abstract

The invention discloses an abnormal relative tendency generation method and system for climate prediction. Performing time smoothing on the original data of the climate variables to remove the high-frequency variation rate; subtracting the climate state of the smooth data to obtain a distance plane; on the basis, according to the target frequency band, selecting the length of the early-stage average time period of each moment, and defining a corresponding recent abnormal background; the recent abnormal background is subtracted, the low frequency variation rate is removed, and the abnormal relative tendency is obtained; and modeling and predicting the abnormal relative tendency, and substituting and adding the low-frequency variation rate as a known recent abnormal background to realize prediction of a distance and an original field. According to the method, the problems of time boundary and multi-scale of climate prediction are solved, target frequency band information is extracted at the tail end of a time sequence only by using historical and current data, the relative tendency of high-frequency anomaly on a known recent anomaly background can be highlighted, only the relative tendency of anomaly needs to be predicted, errors caused by introduction of prediction low-frequency variation rate are avoided, and the prediction accuracy is improved. And the accuracy and the stability of climate prediction are effectively improved.

Description

Technical field [0001] The present invention belongs to the field of digital signal processing and climate prediction, and more particularly to the target band information extraction method of history and current data and the climate prediction method based on the method, can be used for a variety of time scale of the season, the secondary season. predict. Background technique [0002] Existing common filtering methods for climate research. Climate research often pays attention to changes in the climate system in certain specific frequency bands, to extract information on the frequency band, weaken other frequency bands to the study, need to apply filters for raw data applications. Existing Filters commonly used in climate research mainly include FFT filters (Steinacker, 2021), LANCZOS filter (LANCZOS, 1956; Duchon, 1979) and Butterworth, 1930; Murakami, 1979). The FFT filter belongs to the frequency domain filter, and the discrete Fourier transform is the theoretical basis; the ...

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Application Information

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IPC IPC(8): G06Q10/04G06F17/18
Inventor 杨修群张昱培孙旭光陶凌峰房佳蓓张志琦王昱
Owner NANJING UNIV
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