Geoscience Reference
In-Depth Information
9
Modeling the Arctic Climate System
Overview
Much of our current understanding of the Arctic climate system comes
from numerical models. Numerical modeling experiments help us to
understand interactions and feedbacks between variables and system
components that can be difficult, if often impossible, to address
from observations alone. A powerful tool in this regard is sensitivity
experiments, whereby results from a control simulation, with “standard”
model inputs or boundary conditions (e.g., atmospheric composition,
sea ice extent) are compared to results from simulations in which inputs
or boundary conditions are altered, thereby capturing the importance
of the alteration on the modeled system. From previous chapters, the
reader should already be familiar with some of the applications of
numerical models. In
Chapter 5
, we discussed aspects of cloud radiative
forcing based on output from radiative transfer models.
Chapter 7
briefly
examined the application of thermodynamic models to understand sea
ice growth. Many studies of the atmospheric circulation discussed in
Chapter 4
make use of output from atmospheric reanalysis systems, in
which historical atmospheric and surface observations are assimilated
within a weather prediction model to provide multidecadal gridded
time series of atmospheric and surface variables (e.g., pressure heights,
winds, and humidity at various pressure levels, precipitation, and
evapotranspiration). Reanalyses are especially valuable in Arctic research
as they provide information on variables which are only sparsely
observed, such as precipitation and evapotranspiration.
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