% IMPORTANT: The following is UTF-8 encoded. This means that in the presence
% of non-ASCII characters, it will not work with BibTeX 0.99 or older.
% Instead, you should use an up-to-date BibTeX implementation like “bibtex8” or
% “biber”.
@ARTICLE{Frmming:902280,
author = {Frömming, Christine and Grewe, Volker and Brinkop, Sabine
and Jöckel, Patrick and Haslerud, Amund S. and Rosanka,
Simon and van Manen, Jesper and Matthes, Sigrun},
title = {{I}nfluence of weather situation on
$non-{CO}\<sub\>2\</sub\>$ aviation climate effects: the
{REACT}4{C} climate change functions},
journal = {Atmospheric chemistry and physics},
volume = {21},
number = {11},
issn = {1680-7324},
address = {Katlenburg-Lindau},
publisher = {EGU},
reportid = {FZJ-2021-04143},
pages = {9151 - 9172},
year = {2021},
abstract = {Emissions of aviation include CO2, H2O, NOx, sulfur oxides,
and soot. Many studies have investigated the annual mean
climate impact of aviation emissions. While CO2 has a long
atmospheric residence time and is almost uniformly
distributed in the atmosphere, non-CO2 gases and particles
and their products have short atmospheric residence times
and are heterogeneously distributed. The climate impact of
non-CO2 aviation emissions is known to vary with different
meteorological background situations. The aim of this study
is to systematically investigate the influence of
characteristic weather situations on aviation climate
effects over the North Atlantic region, to identify the most
sensitive areas, and to potentially detect systematic
weather-related similarities. If aircraft were re-routed to
avoid climate-sensitive regions, the overall aviation
climate impact might be reduced. Hence, the sensitivity of
the atmosphere to local emissions provides a basis for the
assessment of weather-related, climate-optimized flight
trajectory planning. To determine the climate change
contribution of an individual emission as a function of
location, time, and weather situation, the radiative impact
of local emissions of NOx and H2O to changes in O3, CH4, H2O
and contrail cirrus was computed by means of the
ECHAM5/MESSy Atmospheric Chemistry model. From this,
4-dimensional climate change functions (CCFs) were derived.
Typical weather situations in the North Atlantic region were
considered for winter and summer. Weather-related
differences in O3, CH4, H2O, and contrail cirrus CCFs were
investigated. The following characteristics were identified:
enhanced climate impact of contrail cirrus was detected for
emissions in areas with large-scale lifting, whereas low
climate impact of contrail cirrus was found in the area of
the jet stream. Northwards of 60∘ N, contrails usually
cause climate warming in winter, independent of the weather
situation. NOx emissions cause a high positive climate
impact if released in the area of the jet stream or in
high-pressure ridges, which induces a south- and downward
transport of the emitted species, whereas NOx emissions at,
or transported towards, high latitudes cause low or even
negative climate impact. Independent of the weather
situation, total NOx effects show a minimum at ∼250 hPa,
increasing towards higher and lower altitudes, with
generally higher positive impact in summer than in winter.
H2O emissions induce a high climate impact when released in
regions with lower tropopause height, whereas low climate
impact occurs for emissions in areas with higher tropopause
height. H2O CCFs generally increase with height and are
larger in winter than in summer. The CCFs of all individual
species can be combined, facilitating the assessment of
total climate impact of aircraft trajectories considering
CO2 and spatially and temporally varying non-CO2 effects.
Furthermore, they allow for the optimization of aircraft
trajectories with reduced overall climate impact. This also
facilitates a fair evaluation of trade-offs between
individual species. In most regions, NOx and contrail cirrus
dominate the sensitivity to local aviation emissions. The
findings of this study recommend considering weather-related
differences for flight trajectory optimization in favour of
reducing total climate impact.},
cin = {IEK-8},
ddc = {550},
cid = {I:(DE-Juel1)IEK-8-20101013},
pnm = {2111 - Air Quality (POF4-211)},
pid = {G:(DE-HGF)POF4-2111},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000663965000002},
doi = {10.5194/acp-21-9151-2021},
url = {https://juser.fz-juelich.de/record/902280},
}