Title: Ensemble-based approximation of observation impact using an observation-based verification metric

Author: Matthias Sommer (Ludwig-Maximilians-Universität München)
Martin Weissmann (Ludwig-Maximilians-Universität München)

The benefits of evaluating the impact of observations onto the forecast error have recently been demonstrated in a series of publications. Here a modification of an existing method for computing observation impact in an ensemble based data assimilation and forecasting system is presented and applied to a pre-operational, convective-scale model (COSMO-DE). Instead of the analysis, this modified approach employs an observation-based verification metric to mitigate the effect of correlation between the forecast and its verification. Furthermore, a peculiar property in the probability distribution of observation impact is used to define a measure for the accuracy of the impact assessment. Applying this method to a three days test period shows that a well-defined observation impact value can be assigned to most observation groups and the reliability indicator successfully depicts where results are not significant.

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

Curator: Nikki Privé Last Updated: Feb 9 2015