Data assimilation combines observational data and numerical modelling. It is commonly used in numerical weather prediction, but is also applied in oceanography, hydrology and many other areas of Earth system science. By integrating observations with models in a quantitative way, data assimilation allows to estimate model states with reduced uncertainty, e.g. to initialise model forecasts. Also, data assimilation can estimate parameters that control processes in the model or fluxes, which can be difficult to measure. The combination of modelled and observed data requires error estimates for both sources of information. In ensemble data assimilation the error in the model state is estimated by an ensemble of model state realisations. This ensemble provides estimates of uncertainties and of cross-correlations between different model variables or parameters.
To simplify the implementation and use of ensemble data assimilation the Parallel Data Assimilation Framework (PDAF) has been developed at the Alfred Wegener Institute. PDAF is a freely available open-source software (http://pdaf.awi.de) that provides ensemble-based data assimilation methods and allows to perform pure ensemble simulations. PDAF is designed to be used for small toy problems running on notebook computers up to high-dimensional Earth system models running on supercomputers.
Dr. Lars Nerger from the Alfred Wegener Institute and colleagues from the University of Reading and the Deutscher Wetterdienst are offering a short course on Data Assimilation with PDAF at the upcoming EGU General Assembly 2019 in Vienna. This course is directed to both newbies as well as data-assimilation experts and will include an introduction to the ensemble data assimilation methodology, the implementation concept of PDAF and hands-on examples of building a data assimilation system based on a numerical model. This practical introduction will prepare the participants to build a data assimilation system for their numerical models with PDAF and hence provide a quick start for applying ensemble data assimilation to a variety of cases.
The course will be held on Thursday, 11 April 2019, at 14:00–15:45 in Room -2.85 at the Austria Center Vienna, the conference venue. More information can be found at: https://meetingorganizer.copernicus.org/EGU2019/session/31044