HR: 11:00h
AN: A32A-03    [Abstracts]
TI: Prediction of Sub-seasonal Atmospheric Variability Using Coupled-Multi-Model Superensemble
AU: * Vijaya Kumar, T
EM: vijay@met.fsu.edu
AF: Florida State University, Department of Meteorology The Florida State University, Tallahassee, Fl 32306-4520 United States
AU: Krishnamurti, T
EM: tnk@io.met.fsu.edu
AF: Florida State University, Department of Meteorology The Florida State University, Tallahassee, Fl 32306-4520 United States
AB: Seasonal forecast data sets from four different versions of the Florida State University (FSU) coupled model are examined to study the predictability issues of sub-seasonal atmospheric variability on the time scales of Madden-Julian Oscillations (MJO) and Intra-Seasonal Oscillations (ISO). These four versions of the coupled model are identical except for the choice of parameterization schemes for cumulus convection and radiative transfer. As many as 720 seasonal forecast experiments were carried out with these models for the period from 1987 to 2002. The multimodel superensemble methodology developed at the FSU has shown some promising results in the areas of numerical weather prediction, hurricane track and intensity forecasts, and seasonal climate forecasts. This methodology is extended to the FSU coupled model daily forecast data sets in order to examine the predictability issues on the sub-seasonal time scales. The results of this study are encouraging, where the superensemble forecasts show higher skill in predicting these low-frequency modes compared to individual member models and the conventional ensemble mean. Some episodes of MJO and ISO are examined in detail and the deterministic and probabilistic skills are evaluated using standard measures for verification.
DE: 3337 Numerical modeling and data assimilation
DE: 3339 Ocean/atmosphere interactions (0312, 4504)
DE: 4215 Climate and interannual variability (3309)
SC: Atmospheric Sciences [A]
MN: 2005 Joint Assembly