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@ARTICLE{vanNoije:56573,
author = {van Noije, T. P. C. and Eskes, H.J. and Dentener, F. J. and
Stevenson, D. S. and Ellingsen, K. and Schultz, M. G. and
Wild, O. and Amann, M. and Atherton, C. S. and Bergmann, D.
J. and Bey, I. and Boersma, K. F. and Butler, T. and Cofala,
J. and Drevet, J. and Fiore, A. M. and Gauss, M. and
Hauglustaine, D. A. and Horowitz, L. W. and Isaksen, I. S.
A. and Krol, M. C. and Lamarque, J.-F. and Lawrence, M. G.
and Martin, R. V. and Montanaro, V. and Müller, J.-F. and
Pitari, G. and Prather, M. J. and Pyle, J. A. and Richter,
A. and Rodriguez, J. M. and Savage, N. H. and Strahan, S.E.
and Sudo, K. and Szopa, S. and van Roozendael, M.},
title = {{M}ulti-model ensemble simulations of troposphere {NO}2
compared with {GOME} retrievals for the year 2000},
journal = {Atmospheric chemistry and physics},
volume = {6},
issn = {1680-7316},
address = {Katlenburg-Lindau},
publisher = {EGU},
reportid = {PreJuSER-56573},
pages = {2943 - 2979},
year = {2006},
note = {Record converted from VDB: 12.11.2012},
abstract = {We present a systematic comparison of tropospheric NO2 from
17 global atmospheric chemistry models with three
state-of-the-art retrievals from the Global Ozone Monitoring
Experiment (GOME) for the year 2000. The models used
constant anthropogenic emissions from IIASA/EDGAR3.2 and
monthly emissions from biomass burning based on the 1997 -
2002 average carbon emissions from the Global Fire Emissions
Database (GFED). Model output is analyzed at 10: 30 local
time, close to the overpass time of the ERS-2 satellite, and
collocated with the measurements to account for sampling
biases due to incomplete spatiotemporal coverage of the
instrument. We assessed the importance of different
contributions to the sampling bias: correlations on seasonal
time scale give rise to a positive bias of 30 - $50\%$ in
the retrieved annual means over regions dominated by
emissions from biomass burning. Over the industrial regions
of the eastern United States, Europe and eastern China the
retrieved annual means have a negative bias with significant
contributions ( between - $25\%$ and + $10\%$ of the NO2
column) resulting from correlations on time scales from a
day to a month. We present global maps of modeled and
retrieved annual mean NO2 column densities, together with
the corresponding ensemble means and standard deviations for
models and retrievals. The spatial correlation between the
individual models and retrievals are high, typically in the
range 0.81 - 0.93 after smoothing the data to a common
resolution. On average the models underestimate the
retrievals in industrial regions, especially over eastern
China and over the Highveld region of South Africa, and
overestimate the retrievals in regions dominated by biomass
burning during the dry season. The discrepancy over South
America south of the Amazon disappears when we use the GFED
emissions specific to the year 2000. The seasonal cycle is
analyzed in detail for eight different continental regions.
Over regions dominated by biomass burning, the timing of the
seasonal cycle is generally well reproduced by the models.
However, over Central Africa south of the Equator the models
peak one to two months earlier than the retrievals. We
further evaluate a recent proposal to reduce the NOx
emission factors for savanna fires by $40\%$ and find that
this leads to an improvement of the amplitude of the
seasonal cycle over the biomass burning regions of Northern
and Central Africa. In these regions the models tend to
underestimate the retrievals during the wet season,
suggesting that the soil emissions are higher than assumed
in the models. In general, the discrepancies between models
and retrievals cannot be explained by a priori profile
assumptions made in the retrievals, neither by diurnal
variations in anthropogenic emissions, which lead to a
marginal reduction of the NO2 abundance at 10: 30 local time
( by 2.5 - $4.1\%$ over Europe). Overall, there are
significant differences among the various models and, in
particular, among the three retrievals. The discrepancies
among the retrievals ( 10 - $50\%$ in the annual mean over
polluted regions) indicate that the previously estimated
retrieval uncertainties have a large systematic component.
Our findings imply that top-down estimations of NOx
emissions from satellite retrievals of tropospheric NO2 are
strongly dependent on the choice of model and retrieval.},
keywords = {J (WoSType)},
cin = {ICG-II},
ddc = {550},
cid = {I:(DE-Juel1)VDB48},
pnm = {Atmosphäre und Klima},
pid = {G:(DE-Juel1)FUEK406},
shelfmark = {Meteorology $\&$ Atmospheric Sciences},
typ = {PUB:(DE-HGF)16},
UT = {WOS:000239137200002},
doi = {10.5194/acp-6-2943-2006},
url = {https://juser.fz-juelich.de/record/56573},
}