Title: Ensemble inflation in hybrid data assimilation

Author: Amal El Akkraoui (Science System and Applications, Inc)
Ricardo Todling (NASA/GMAO)

The Global Modeling and Assimilation Office (GMAO) has recently implemented a 3D-Hybrid data assimilation system based on the square root Ensemble Kalman filter of Whitaker and Hamill (2002). To prevent the ensemble from collapsing after repetitive cycles of analysis updates, inflation is used as a way to boost ensemble spread, and to account for some system uncertainties. GMAO currently uses a combination of a relaxation to prior type of inflation (multiplicative), and an additive inflation that uses random samples of forecast error perturbations (drawn similarly to the NMC method). While the former accounts for sampling errors, the latter is supposed to represent model uncertainty in the ensemble. However, generating additive samples from a climatological distribution has no bearing on actual model errors or errors of the day. This work will examine some alternative options to induce and sustain growth and discuss preliminary results of utilizing a Stochastically Perturbed Physics Tendencies (SPPT) scheme.

GMAO Head: Steven Pawson Global Modeling and Assimilation Office NASA Goddard Space Flight Center

Curator: Nikki Privé Last Updated: Feb 9 2015