Stochastic Perturbation Scheme For Representing Model Related
stochastic parameterization scheme is designed for representing model
related errors in ensemble forecasting. The strategy involves the
addition of a stochastic term with structured noise in the tendencies
of each model variable. For each member of the ensemble, the stochastic
forcing is constructed as a random linear combination of tendencies of
ensemble members and the control forecast. The flexible software
infrastructure developed in the Earth System Modeling Framework (ESMF)
collaboration can be employed to synchronize the integration of all
ensemble members and the control run, and facilitate the information
exchange among these runs.
A simplified version of the scheme is tested with the NCEP Global
Ensemble Forecast System (GEFS). Experimental forecasts for October,
2004 show that the scheme can significantly increase the ensemble
spread, with reduced number of outliers and reduced systematic error in
the ensemble mean forecast. The performance of probabilistic forecasts
based on the NCEP global ensemble system is also improved, especially
in terms of Ranked Probability Skill Score (RPSS).
The scheme could also be used in other Earth system modeling
applications such as hydrologic ensemble forecasting.
Dingchen Hou, Zoltan
Toth and Yuejian Zhu