Developing a multi-variable, multi-scale ensemble Kalman filter for global land surface modelling

Global multi-variable data assimilation requires solutions to deal with the different spatial and temporal resolution of different observations. This project will develop a multi-variable, multi-scale ensemble Kalman filter that incorporates improved observation error models and operators, and develops an optimally configured and resolved filter.

This project is in collaboration with Dr Valentijn Pauwels (Monash University).

Candidates should have some experience with scripting languages and programming. A scholarship may be available

For more information about this potential research topic or activity, or to discuss any related research area, please contact the supervisor.

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