JP1.12
Retrospective Time Integration Scheme in Mesoscale Numerical Model
Xiao-Jing Jia, Chinese Academy of Meteorological Sciences, Beijing, China
In view of the fact that the atmospheric motion is an irreversible process , a memory function which can recall the observation data in the past has been introduced , moreover it is a new method of numerical weather forecast which combine dynamic and statistic . retrospective time integration scheme, which is generalized from the traditional difference scheme can improve the forecast accuracy , it contains historical information so this scheme adapts to mesoscale weather forecast . The purpose of this paper is to apply this scheme to MM5 model and validate the efficiency of this scheme .Based on the atmospheric self-memorization principle ,the retrospective time integration scheme in a mesoscale numerical model is established which is called SMM5 , and the experimental result is compared with the kernel model MM5. the data used in this experiment is taken in the rain season , 1998 and we emphasize on analyze the fields of wind , air pressure ,temperature of 700hpa during 16-28 July 1998 and the field of rainfall was studied too , it shows that: Because of using information of several history fields ,SMM5 can improve the prediction accuracy . verified with both correlation coefficient and root-mean-square error , the wind, air pressure, temperature fields predicted with SMM5 are much better than that of MM5 . As to the rainfall field , both the precipitation areas and precipitation intensities of SMM5 is more similar to the observed field than that of MM5.
Joint Poster Session 1, Ensemble Forecasting and Other Topics in Probability and Statistics (Joint with the 16th Conference on Probability and Statistics in the Atmospheric Sciences and the Symposium onObservations, Data Assimilation,and Probabilistic Prediction)
Wednesday, 16 January 2002, 1:30 PM-3:00 PM
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