TITLE:

The keys of ensemble data assimilation

DATE:

Friday, January 30th, 2015

TIME:

3:30 PM

LOCATION:

GMCS 214

SPEAKER:

Dr. Tim Hoar. Institute for Mathematics Applied to Geosciences.

National Center for Atmospheric Research

ABSTRACT:

The main focus of an ensemble data assimilation system is to produce a collection of model states – the ensemble – that is informative and indistinguishable from the modeled physical system. The characteristics of the ensemble must capture and reflect the uncertainty in our knowledge of the system being modeled as well as the variability of the system itself. We know that all models are imperfect. We also know that our knowledge of the initial conditions and forcing for those models is imperfect. The observations of interest may not be represented explicitly in the model and both the model and the observations have uncertainties and differences in representativeness. An effective data assimilation system must address all of these while producing a model state that contains the information that may be derived from those observations. There are many open research questions that need to be addressed to create an assimilation system that performs well. The simple truth is that naive implementations of the admittedly simple ensemble algorithms generally result in significantly sub-optimal results.

This talk will introduce the theory of ensemble data assimilation, the common pitfalls of ensemble data assimilation, and ways to assess the performance of the system to ensure you are getting the most out of the observations. I will use some of the tutorial material from the Data Assimilation Research Testbed (DART) developed and maintained at the National Center for Atmospheric Research (NCAR). DART is a software environment that makes it easy to explore a variety of ensemble data assimilation methods and observations with different numerical models and is designed to facilitate the combination of assimilation algorithms, models, and real (as well as synthetic) observations to allow increased understanding of all three. Examples will come from atmospheric, oceanic, and land surface assimilation experiments.

HOST:

Dr. Jose Castillo

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