Box 1.5. Atmospheric models
The chemical composition and the thermal and dynamical structure of the atmosphere are determined by a large number
of simultaneously operating and interacting processes. Therefore, numerical mathematical models have become indispensable tools to study these complex atmospheric interactions. Scientific progress is achieved in part by understanding the
discrepancies between atmospheric observations and results from the models. Furthermore, numerical models allow us to
make predictions about the future development of the atmosphere. Today, a hierarchy of atmospheric models of increasing complexity is employed for the investigation of the Earth’s atmosphere. Models range from simple (with perhaps one
process or one spatial dimension considered) to the most complex 3-D and interactive models. In the following list, a brief
summary of the most important types of models is given:
• Fixed dynamical-heating (FDH) model: Calculation of stratospheric temperature changes and radiative forcing with a
radiation scheme, assuming that the stratosphere is in an equilibrium state and no dynamical changes occur in the atmosphere.
• Trajectory (Lagrangian) model: Simulation of air-parcel movement through the atmosphere based on meteorological
analyses.
• Box-trajectory model: Simulation of chemical processes within a parcel of air that moves through the atmosphere.
• Mesoscale (regional) model: Analysis and forecast of medium-scale (a few tens of kilometers) radiative, dynamical and
chemical structures in the atmosphere; investigation of transport and exchange processes.
• Contour-advection model: Simulation of highly resolved specific two-dimensional (2-D) fluid-dynamical processes,
such as processes at transport barriers in the atmosphere.
• Mechanistic circulation model: Simplified 3-D atmospheric circulation model that allows for the investigation of specific dynamical processes.
• Two-dimensional photochemistry model: Zonally averaged representation of the middle atmosphere, with detailed
chemistry but highly simplified transport and mixing.
• General-circulation climate model (GCM): Three-dimensional simulation of large-scale radiative and dynamical processes (spatial resolution of a few hundred kilometers) in the atmosphere over years and decades; investigation of the
climate effects of atmospheric trace gases (greenhouse gases); investigations of the interaction of the atmosphere with
the biosphere and oceans.
• Chemistry-transport model (CTM): Three-dimensional (or 2-D latitude-longitude) simulation of chemical processes
in the atmosphere employing meteorological analyses derived from observations or GCMs; simulation of spatial and
temporal development and distribution of chemical species.
• Chemistry-climate model (CCM): Interactively coupled 3-D GCM with chemistry; investigation of the interaction of
radiative, dynamical, physical and chemical processes of the atmosphere; assessment of future development of chemical
composition and climate.
Several decades ago, when numerical models of the atmosphere were first developed, much less computational power was
available than today. Early studies with numerical models focused on the simulation of individual radiative, dynamical or
chemical processes of the atmosphere. These early and rather simple models have evolved today into very complex tools,
although, for reasons of computational efficiency, simplifying assumptions (parametrizations) must still be made. For example, the atmosphere in a global model requires discretization, which is generally done by decomposing it into boxes of
a specific size. Processes acting on smaller scales than the boxes cannot be treated individually and must be parametrized,
that is, their effects must be prescribed by functional dependencies of resolved quantities.
tropopause region. There is an observed relationship between
column ozone and several tropospheric circulation indices, including tropopause height (Section 1.3.4.2). Over time scales of
up to about one month, it is the dynamical changes that cause
the ozone changes (Randel and Cobb, 1994), whereas on longer
time scales feedbacks occur and the causality in the relationship
becomes unclear. Thus, although various tropospheric circulation indices (including tropopause height) have changed over
the last 20 years in the NH in such a way as to imply a decrease
IPCC Boek (dik).indb 111
in column ozone, this inference is based on an extrapolation of
short-time-scale correlations to longer time scales, which may
not be valid (Section 4.6 of WMO, 2003).
Above the tropopause, stratospheric PWD drives the seasonal winter-spring ozone build-up in the extratropics, and has
essentially no interannual memory (Fioletov and Shepherd,
2003). It follows that the observed decrease in NH PWD in the
late winter and spring has likely contributed to the observed decrease in NH column ozone over the last 20 to 25 years (Fusco
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