Dr. Stefan Rüdisühli

Dr. Stefan Rüdisühli

Staff of Professorship for Atmospheric Circulation

ETH Zürich

Center f. Climate Systems Modeling

CHN M 11

Universitätstrasse 16

8092 Zürich

Switzerland

Additional information

Additional information

My main interests are in extratropical weather systems and their analysis in high-resolution simulation data. Specifically, I am investigating fronts and precipitation over Europe, and how they relate to each other.

Tracked fronts for storm Lancelot (animation)
Animation of tracked fronts for winter storm Lancelot, January 19-21 2007. (Left) Synoptic situation with total cloud cover (grey-white) overlaid with Z850 (contours) and hourly precipitation (colors). (Right) Tracked fronts colored with front velocity with red/blue indicating warm/cold frontal character (colorbar missing). Front outlines are colored with total track duration in hours (colorbar). Circular black outlines indicate raw cyclone features.

A decade of European weather at 2.2 km

My PhD project is part of the interdisciplinary project crCLIM, whose goal is to run decade-long convection-resolving (2.2. km) simulations over Europe using the COSMO modelcall_made on GPUs, with most analysis conducted on-the-fly to avoid immense amounts of data output. I am analyzing weather phenomena such as fronts and precipitation in these simulations from a feature-based perspective, in order to create deade-long high-resolution climatologies.

Precipitation

To investigate precipitation events, I track surface precipitation features over time (see below). Attribution to fronts (see below) allows me to distinguish frontal and nonfrontal precipitation. As a first result, the following figure shows diurnal cycle composites of precipitation anomalies. Nonfrontal precipitation shows a diurnal cycle with prominent maxima over the continents in the afternoon and evening, and weaker maxima over the oceans during the night. The frontal precipitation composites show no diurnal cycle, which validates our attribution technique.

Composites of (top) nonfrontal and (bottom) frontal precipitation anomalies above baseline in log10(mm/hr/month) for the 6 hourly windows (left to right) 00-05, 06-11, 12-17, and 18-23 UTC for the year 2007.

Fronts

To automatically detect fronts fronts, I first apply an established method based on ∇θe (Jenkner et al. 2010) to obtain raw front fields, to which I subsequently apply feature tracking (see below). Track analysis then allows me to distinguish between meso-/synoptic-scale fronts, in which I am interested, and near-surface ∇θe structures that develop near orography or convective cells due to the high model resolution.

Feature tracking

To obtain information about the temporal development of features, I track them, which involves following them through time and space. Due to the high temporal and spatial resolution of our simulation, features change little in position and size between consecutive analysis timesteps. This allows me to base our purely diagnostic tracking algorithm on a relatively simple combination of overlap and size criteria. To account for interactions of multiple features, the algorithm support mergings and splittings. The main components of a feature track are illustrated in the following schematic.

Components of a feature track that contains multiple branchings, each of which involves one parent (red) and multiple child features (green). Branchings pointing backward/forward in time are denoted mergings/splittings.
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