1. Supervisors : Alan Gadian, Sarah-Jane Lock, Andrew Ross
Development and investigation of a new numerical technique for simulating flow over steep terrain
Beth Good
Supervisors : Alan Gadian,
Sarah-Jane Lock,
Andrew Ross

2. 2007-2010 - BSc Mathematics from Warwick
MSc Atmosphere Oceans and climate Reading
Started PhD at Leeds looking at simulating flow over steep terrain.

3. Introduction
The shape of the underlying surface has an effect on the local and in some cases synoptic weather.
Mountain ranges channel and direct winds.
Produce rain shadows down stream
Large down slope winds
Foehn effect – fires
Set up waves which can propogate for miles downstream. e.g. Rocky’s

4. Terrain Following Approach
Models commonly use terrain
following coordinates to
represent the surface.
Where there are steep gradients errors occur in the computation of the horizontal component of the pressure gradient force.
These errors impact on the winds and can lead to
Generation of spurious winds in the vicinity of mountains (Jebens et al, 2011)
Incorrect cloud structure and precipitation patterns. E.g. The LM-tf model systematically fails to forecast low stratus north of the Alps in low wind situations. (Steppeler et al, 2006)
The higher the resolution of the model the more the detail of the orography influences the simulated atmospheric processes

5. Cut-cell Approach The vertical levels are horizontal.
The terrain intersects the grid.
More accurate representation of the horizontal pressure gradient.
In theory avoids errors found in terrain following models.
Representation of terrain in a cut-cell model

6. Resting Atmosphere Test
Terrain Following Models
Cut-cell Model
Figure 5: Maximum vertical velocities from four terrain following models. (Klemp,MWR, 2011)
Figure 6: Maximum vertical velocity with time from the Cut-cell model
Best case - maximum velocity 10-2 m/s
Less sophisticated models m/s
Maximum velocity – m/s
Due to machine accuracy

7. Thanks for Listening