We are offering a research internship (4 months, with the possibility of a part-time contract) to analyse the benefits that improved representation of biomass burning emissions has on the predictive skill of the ECMWF seasonal forecast system, paying special attention to the most important wild fires events that occurred in the last decade. This position will be jointly hosted by the Climate Variability and Change Group within BSC’s Earth Science Department.
The successful candidate will analyse three sets of retrospective seasonal predictions performed with different implementations of the forcing due to biomass burning emissions, and apply tailored statistical techniques to determine the predictive skill of each system, and identify the improvements enabled by the most realistic forcing implementation. This work will contribute to the H2020 project CONFESS, seeking to produce a more consistent representation of the temporal variations in the boundary forcings used to produce the reanalyses and the seasonal forecast with the ECMWF systems.
Key Duties
- Compute the seasonal predictive skill for the main climatic variables (surface temperature, precipitation and sea level pressure) in the three seasonal prediction systems
- Estimate the differences in skill between the different forecast systems
- Compare the different forecasts for several recent extreme wild fire events
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