Climate models and Numerical Weather Prediction (NWP) Models describe the atmospheric circulation with a
limited resolution. There unavoidably remains processes that involve spatial scales shorter than the
grid scales, ie processes that are unresolved. Cloud processes, turbulence near the surface and internal
gravity waves propagating from lower to upper layers are among the main dynamical...
In this talk I will first introduce the basics of radar imaging and present some applications
for climate science. I will then show how machine learning can make a key contribution
to improve radar data degraded by the speckle phenomenon and extract useful information.
I will focus on self-supervised methods allowing for exploiting a wide range of unlabeled data.