Hello, my name is Manuel and I work at the FAU in Erlangen within the international doctorate

program MOCHA.

In my research I look at drifting snow.

So when winds are strong enough, snow can be eroded from the ground, can be transported

by the wind over large distances and is eventually deposited in areas that are sheltered from

the wind.

This can lead to very complex patterns in snow depth and because of this complexity

the drifting snow is not yet included in most of the glacial mass balance models.

In our group we have built a new sub-model into a widely used numerical weather prediction

model and we can use this model to calculate drifting snow.

We saw that this model can be a very powerful tool for short case studies and we can gain

new insights into the processes that are involved.

However, when we want to look at longer time series or at larger areas then the computations

get much too expensive.

And therefore we are currently working on a so-called emulator model which is a machine

learning model that is trained with simulated data from the numerical model and learns to

emulate the predictions from the numerical model just at a much lower computation cost.

And with this model we want to be able to assess how important the drifting snow is

for glaciers in different environments all over the world and on a seasonal to even longer

time scale.

For me the great thing about the doctorate program is that we have so many people from

different disciplines and different backgrounds working together and on the one hand these

different perspectives can help me in my model development and on the other hand we have

already people that can directly make use of my model and can validate it in nature.