Turbulent confetti
To diffuse or not to diffuse
Intuitive probabilistic meteograms
To rain or not to rain.
The harmonic sum with posits
One plus tiny plus tiny ... equals big!
MPI-Parallelization in Julia: A 1D shallow water example.
Domain decomposition 101: Shared work is half the work.
Turbulence Topography
How to visualize the surface of turbulence?
Juls - The first 16bit Atmosphere/Ocean Model
Juls is great. No probably it's not, at least not yet. But, it can simulate geostrophic turbulence typical for either atmospheric or oceanic flow with 16bit numbers. Indeed 16bit. Usually climate models use 64bit numbers. Why?
A posit of posits: 4 bits better.
Who wins if Bart Simpson, Son Goku and Johnny Bravo fight about decimal precision? And why on Earth is that related to their haircuts?
How does a running mean affect correlation?
In many climate science studies a running mean filter is used as a low-pass filter. Authors then usually claim to find some large scale (e.g. decadal) co-variability based on running mean-filtered time series. What's the problem with that?
Reynolds, Rossby and Ekman
What are the structures of Reynolds, Rossby and Ekman numbers in geostrophic turbulence?
Removing the seasonal cycle
How to identify the seasonal cycle from a time series?
Topography and color vision deficiency: Intuitive colormaps
A story on how to plot topographic data intuitively and easily understandable also for non-scientists and people with color vision deficiency (CVD): Just because you find it pretty, it's not necessarily pretty through everyone's eyes.
Visualization of 2D turbulence
Taking the curl of the 2D Euler equations yields an equation with relative vorticity as prognostic variable. A numerical model can solve these equations and provides a wonderful insight into the vorticity dynamics in 2D turbulence. In
Shallow water model
For my Masters thesis I used a shallow water model in order to investigate energy-budget based backscatter parametrization for unresolved eddies. I wrote the numerical model in Python in 2016 and although idealized, it involves some features to mention,
Implementing level set methods into a 2D Boussinesq model
Tracking surfaces is a challenging issue for a realistic simulation of fluids in interaction with other fluids or solid objects. Level set methods is the state of the art methodology to discretize the movement of a surface in any kind of flow field
Brownian motion
Simulating Brownian motion was a self-chosen mini-project at the beginning of my PhD. You can find the model on github. An adaptive time stepping scheme is used, where the particles trajectories to collision are predicted
Simple Finite-Element model for steady Navier-Stokes equations
The present study introduces the Finite Element Methods in theory and describes its implementation for an idealized two dimensional test case. The equations of interest are the Navier-Stokes equations, describing the conservation of momentum for fluid flows.