Atmospheric Chemistry and Physics
www.atmos-chem-phys.net
1680-7316
1680-7324
10
4
2010
10.5194/acp-10-1931-2010
http://www.atmos-chem-phys.net/10/1931/2010/
http://www.atmos-chem-phys.net/10/1931/2010/acp-10-1931-2010.html
http://www.atmos-chem-phys.net/10/1931/2010/acp-10-1931-2010.pdf
1931
1951
2010-02-19
Uncertainties in atmospheric chemistry modelling due to convection parameterisations and subsequent scavenging
H. Tost
holger.tost@mpic.de
M. G. Lawrence
C. Brühl
P. Jöckel
The GABRIEL Team
The SCOUT-O3-DARWIN/ACTIVE Team
Atmospheric Chemistry Department, Max Planck Institute for Chemistry, P.O. Box 3060, 55020 Mainz, Germany
EEWRC, The Cyprus Institute, Nicosia, Cyprus
Consortium of MPI for Chemistry, Enviscope, MDS, KNMI, STINASU
Consortium of over 75 atmospheric research institutes worldwide
now at: Deutsches Zentrum für Luft-und Raumfahrt (DLR), Institut für Physik der Atmosphäre, Oberpfaffenhofen, 82234 Weßling, Germany
Moist convection in global modelling contributes significantly to the
transport of energy, momentum, water and trace gases and aerosols within
the troposphere. Since convective clouds are on a scale too small to be
resolved in a global model their effects have to be parameterised.
However, the whole process of moist convection and especially its
parameterisations are associated with uncertainties.
In contrast to previous studies on the impact of convection on trace
gases, which had commonly neglected the convective transport for some or
all compounds, we investigate this issue by examining simulations with
five different convection schemes.
This permits an uncertainty analysis due to the process formulation,
without the inconsistencies inherent in entirely neglecting deep
convection or convective tracer transport for one or more tracers.
<br><br>
Both the simulated mass fluxes and tracer distributions are analysed.
Investigating the distributions of compounds with different characteristics,
e.g., lifetime, chemical reactivity, solubility and source
distributions, some differences can be attributed directly to the
transport of these compounds, whereas others are more related to
indirect effects, such as the transport of precursors, chemical reactivity in
certain regions, and sink processes.
<br><br>
The model simulation data are compared with the average regional
profiles of several measurement campaigns, and in detail with two
campaigns in fall and winter 2005 in Suriname and Australia, respectively.
<br><br>
The shorter-lived a compound is, the larger the differences and
consequently the uncertainty due to the convection parameterisation are,
as long as it is not completely controlled by local production that is
independent of convection and its impacts (e.g. water vapour changes).
Whereas for long-lived compounds like CO or O<sub>3</sub> the mean
differences between the simulations are less than 25%), differences
for short-lived compounds reach up to ±100% with different
convection schemes.
<br><br>
A rating of an overall "best" performing scheme is difficult, since the optimal performance depends on the region
and compound.
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