A Regional Climate Model (RCM) is a comprehensive tool to
simulate high-resolution climatic factors. A RCM is driven
by low resolution data obtained from a Global Climate Model
(GCM). In the one-way nested method, is the GCM data fed
into the RCM as a Lateral Boundary Condition (LBC) in certain
updates in time, the boundary data interval resolution.
The necessary information in between these updates is obtained
by using linear interpolation techniques. The ability
to reproduce high-resolution RCM output with low-resolution
GCM data depends on the accuracy of this LBC. This thesis
investigates whether third order interpolation methods lead to
a more accurate approximation than the linear method. This is
investigated in combination with lowering the boundary data
interval resolution.
The conclusion is that a third order interpolation method does
not lead to a more accurate approximation for a high boundary
data interval resolution. But when the resolution is lowered,
the linear interpolation method looses its accuracy earlier
than the third order method. This results in a boundary data
interval resolution of 1.5 hours for the linear method compared
to 7.5 hours for the third order method. Implementing
a lower boundary data interval resolution in combination with
the third order method lead to significant gain in computational
time and storage for the RCMs.