NEW APPROACH TO DYNAMIC DATA MODELING AND ITS APPLICATION TO PRECIPITATION FORECASTING

Jia Xiaojing; Cao Hongxing; Feng Guolin

Vol.13, NO.1, 2002

Article Contents

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Jia Xiaojing, Cao Hongxing, Feng Guolin. New approach to dynamic data modeling and its application to precipitation forecasting. J Appl Meteor Sci, 2002, 13(1): 96-101.

Citation:

Jia Xiaojing, Cao Hongxing, Feng Guolin. New approach to dynamic data modeling and its application to precipitation forecasting. J Appl Meteor Sci, 2002, 13(1): 96-101.

Jia Xiaojing, Cao Hongxing, Feng Guolin. New approach to dynamic data modeling and its application to precipitation forecasting. J Appl Meteor Sci, 2002, 13(1): 96-101.

Citation:

Jia Xiaojing, Cao Hongxing, Feng Guolin. New approach to dynamic data modeling and its application to precipitation forecasting. J Appl Meteor Sci, 2002, 13(1): 96-101.

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NEW APPROACH TO DYNAMIC DATA MODELING AND ITS APPLICATION TO PRECIPITATION FORECASTING

1.
Chinese Academy of Meteorological Sciences, Beijing 100081
2.
Department of Physical College, Y angz hou University, Y angzhou 225009

Received Date: 2000-04-03
Rev Recd Date: 2000-07-13
Publish Date: 2002-02-28

Abstract

Abstract

By use of an observed data series a new dynamic data modeling has been proposed. Taking a nonlinear ordinary differential equation which is retrieved from the data series based on the bilateral difference principle as a dynamic kernel, with the self-memorization principle a forecast model can be established, which is called the DAta-based Mechanistic Self-memory Model (DAMSM). Some computing cases show that the forecasting accuracy of the DAMSM is quite satisfactory. An example of inter-annual precipitation prediction in summer in the Yangtze delta is given.
- Self-memory;
- Time series;
- Inter-annual precipitation prediction;
- Flood season precipitation

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References(6)

Figures and Tables

图 1 DAMSM 模式对1969~1998 年降水量的拟合预报与实际降水量的比较

(实线表示DAMSM 模式降水量，虚线表示实际降水量)

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References

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