What will you be doing?
KNMI develops weather and climate models in order to improve forecasts and explore past and future climates. These models contain numerous parameters. The values of these parameters are uncertain. Forecast skill and projected climate changes depend on these values. Modelers lack algorithms that find parameter values that optimize forecast skill and minimize model biases.
In this project we apply a promising new automatic tuning algorithm to the parameters of the world-leading weather forecasting system, the IFS model of the European Centre for Medium Range Weather Forecasts (ECMWF). This model is part of the global climate model EC-Earth that we co-develop and use in our climate modeling group. This project is part of the multi-year strategic research programme at KNMI. We aim to publish the results in scientific peer-reviewed journals and contribute to improve the forecast skill of IFS and the climate projections of EC-Earth.
You will implement the algorithm in the IFS model and perform tuning experiments in order to assess the ability of the algorithm to find optimal parameter values automatically. You will join the enthusiastic research team working on this project and will be part of the ‘global climate’ cluster of the RDWK department.Also you will interact with modelers at KNMI, ECMWF and with the European consortium that develops EC-Earth and with scientists that work on the assimilation of scatterometer winds in weather models.
This gives you energy
The aim is to implement the algorithm and adjust parameters in order to be able to reduce the biases in surface winds by making use of the scatterometer wind product obtained from satellite observations. The algorithm synchronizes the model evolution with observations and learns parameters on the basis of the synchronization errors. With your dedication, which demands a comprehensive comprehension of vertical momentum transfer in the atmosphere through convective and turbulent processes, as well as its impact on the lifecycle of storms, you derive motivation from achieving successful implementation.
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