P1.11
New Approach Of Dynamic Data Modeling and Its Application to Precipitation Forecasting
XiaoJing Jia, Chinese Academy of Meteorological Sciences, Beijing, China
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 kernal, with the self-memorization principle one can establish a forecast model,which is called data-based mechanistic self-memory model (abbreviation DAMSM) .Some computing cases show that the forecasting accuracy of the DAMSM is quite satisfactory,the inter-annual precipitation forecast insummer over Yangtze Delta is presented.
Poster Session 1, Effective Assimilation of the Vast Observational Datasets Becoming Available
Monday, 14 January 2002, 3:30 PM-5:30 PM
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