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On Spatiotemporal Series Analysis and Its Application to Predict the Regional Short Term Climate Process


doi: 10.1007/BF02915717

  • Based on the theory of reconstructing state space, a technique for spatiotemporal series prediction is presented. By means of this technique and NCEP/NCAR data of the monthly mean geopotential height anomaly of the 500-hPa isobaric surface in the Northern Hemisphere, a regional prediction experiment is also carried out. If using the correlation coefficient R between the observed field and the prediction field to measure the prediction accuracy, the averaged R given by 48 prediction samples reaches 21%, which corresponds to the current prediction level for the short range climate process.
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Manuscript History

Manuscript received: 10 March 2004
Manuscript revised: 10 March 2004
通讯作者: 陈斌, bchen63@163.com
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On Spatiotemporal Series Analysis and Its Application to Predict the Regional Short Term Climate Process

  • 1. Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029,Institute of Atmospheric Physics,Chinese Academy of Sciences,Beijing 100029

Abstract: Based on the theory of reconstructing state space, a technique for spatiotemporal series prediction is presented. By means of this technique and NCEP/NCAR data of the monthly mean geopotential height anomaly of the 500-hPa isobaric surface in the Northern Hemisphere, a regional prediction experiment is also carried out. If using the correlation coefficient R between the observed field and the prediction field to measure the prediction accuracy, the averaged R given by 48 prediction samples reaches 21%, which corresponds to the current prediction level for the short range climate process.

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