% 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”.
@PHDTHESIS{Lyapina:202685,
author = {Lyapina, Olga},
title = {{C}luster analysis of {E}uropean surface ozone observations
for evaluation of {MACC} reanalysis data},
volume = {265},
school = {Universität Bonn},
type = {Dr.},
address = {Jülich},
publisher = {Forschungszentrum Jülich GmbH Zentralbibliothek, Verlag},
reportid = {FZJ-2015-04869},
isbn = {978-3-95806-060-9},
series = {Schriften des Forschungszentrums Jülich Reihe Energie $\&$
Umwelt / Energy $\&$ Environment},
pages = {187 S.},
year = {2015},
note = {Universität Bonn, Diss., 2014},
abstract = {The high density of European surface ozone monitoring sites
offers good opportunities for investigation of the regional
ozone representativeness and for evaluation of chemistry
climate models. In this thesis we analyze both aspects with
close relation of one to another. As starting point we
analyze ozone trends and the seasonal behavior of ozone
concentrations at selected individual stations in different
regions of Europe. At this step we are interested to find
out how the observed long-term trends in surface ozone
concentrations are consistent across stations, and would the
annual ozone behaviour give any distinctive patterns within
Europe. The next analysis is extended to seasonal-diurnal
ozone variations, which appear as the main components of
ozone time series and therefore allow to describe the ozone
behavior more comprehensively. The regional
representativeness of European ozone measurements is
investigated through a cluster analysis (CA) of ozone air
quality data from 1492 European surface monitoring stations
(Airbase database). K-means clustering is implemented for 3
sets of properties: (i) seasonal-diurnal variations in
absolute mixing ratio units, (ii) normalized
seasonal-diurnal variations, and (iii) averaged and
normalized seasonal and diurnal variations. Each CA
identifies different ozone pollution regimes, and each of
them is compared with the output of the multi-year global
reanalysis produced within the Monitoring of Atmospheric
Composition and Climate (MACC) project. Recent methods for
evaluation of global chemistry-climate models often provide
only the comparison of the simulated output mean to
individual ozone observations or arbitrarily aggregated sets
of observations. This can give general information about the
model biases for area, captured bysites, but does not help
in the interpretation of these biases. Our CA approach
yields useful information for the evaluation of numerical
models, as it allows for a pre-selection of stations and
uses clusters as means to stratify the comparison with the
respective model output. Comparing the MACC data to cluster
results allows to see whether the model is able to capture
specifics of each group and how well it describes the
various ozone pollution regimes. The selected parameters for
the investigation of ozone representativeness provide
several possibilities to distinguish representative groups
of ozone over Europe. Relying on the most stable conditions,
there are 5 and 4 clusters which adequately describe the
seasonal-diurnal ozone European patterns in case of absolute
and normalized properties, respectively. Comparison of the
model with observations for individual clusters reveal first
of all different overestimation biases, and secondly
differences mainly in seasonal ozone behavior. These biases
are mostly driven by summertime ozone rather than
wintertime, where ozone is generally well predicted. Such
biases decrease from more polluted clusters to cleaner ones.
Also the seasonal and diurnal cycles are described better
for clusters with relatively clean signatures. The best fit
is observed for clusters, which stations are influenced more
by regional rather than local factors.},
cin = {IEK-8},
cid = {I:(DE-Juel1)IEK-8-20101013},
pnm = {243 - Tropospheric trace substances and their
transformation processes (POF3-243) / MACC II - Monitoring
Atmospheric Composition and Climate Interim Implementation
(283576)},
pid = {G:(DE-HGF)POF3-243 / G:(EU-Grant)283576},
typ = {PUB:(DE-HGF)11 / PUB:(DE-HGF)3},
urn = {urn:nbn:de:0001-2015071615},
url = {https://juser.fz-juelich.de/record/202685},
}