Multi-scale

p1-15 January 21 15:10-16:10

Handling time auto-correlated model error in the Ensemble Kalman Smoother

Javier Amezcua (University of Reading, UK National Centre for Earth Observation) Peter Jan van Leeuwen (University of Reading, Colorado State University)

Abstract

The explicit consideration of model error in data assimilation is increasing. While this improves the realism of the situation (i.e. models have deficiencies), it also increases the complexity of the problem. Two common situations are often explored: independent model errors every time step (easy to study in theory) and fixed model errors (easy to implement in practice). We present the solution for an (ensemble) Kalman smoother in the presence of auto-correlated model error with a general (non-zero and non-infinite) memory. Moreover, we study the consequences of using a wrongly guessed memory in the data assimilation which is different from the true memory of the system.

Contact information

Dr. Javier Amezcua University of Reading