cluster analysis of european surface ozone observations for evaluation of macc reanalysis data
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2016
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Abstract
The high density of European surface ozone monitoring sites provides unique
opportunities for the investigation of regional ozone representativeness and
for the evaluation of chemistry climate models. The regional
representativeness of European ozone measurements is examined through a
cluster analysis (CA) of 4 years of 3-hourly ozone data from 1492
European surface monitoring stations in the Airbase database; the time
resolution corresponds to the output frequency of the model that is compared
to the data in this study. K-means clustering is implemented for
seasonal–diurnal variations (i) in absolute mixing ratio units and
(ii) normalized by the overall mean ozone mixing ratio at each site.
Statistical tests suggest that each CA can distinguish between four and five
different ozone pollution regimes. The individual clusters reveal differences
in seasonal–diurnal cycles, showing typical patterns of the ozone behavior
for more polluted stations or more rural background. The robustness of the
clustering was tested with a series of k-means runs decreasing randomly the
size of the initial data set or lengths of the time series. Except for the Po
Valley, the clustering does not provide a regional differentiation, as the
member stations within each cluster are generally distributed all over
Europe. The typical seasonal, diurnal, and weekly cycles of each cluster are
compared to the output of the multi-year global reanalysis produced within
the Monitoring of Atmospheric Composition and Climate (MACC) project. While
the MACC reanalysis generally captures the shape of the diurnal cycles and
the diurnal amplitudes, it is not able to reproduce the seasonal cycles very
well and it exhibits a high bias up to 12 nmol mol−1. The bias
decreases from more polluted clusters to cleaner ones. Also, the seasonal and
weekly cycles and frequency distributions of ozone mixing ratios are better
described for clusters with relatively clean signatures. Due to relative
sparsity of CO and NOx measurements these were not included in the
CA. However, simulated CO and NOx mixing ratios are
consistent with the general classification into more polluted and more
background sites. Mean CO mixing ratios are within 140–145 nmol mol−1
(CL1–CL3) and 130–135 nmol mol−1 (CL4 and CL5), and NOx mixing
ratios are within 4–6 nmol mol−1 and 2–3 nmol mol−1,
respectively. These results confirm that relatively coarse-scale global
models are more suitable for simulation of regional background
concentrations, which are less variable in space and time. We conclude that
CA of surface ozone observations provides a powerful and robust
way to stratify sets of stations, being thus more suitable for model
evaluation.
| Reference Key |
lyapina2016atmosphericcluster
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|---|---|
| Authors | ;O. Lyapina;M. G. Schultz;A. Hense |
| Journal | Journal of agricultural and food chemistry |
| Year | 2016 |
| DOI |
10.5194/acp-16-6863-2016
|
| URL | |
| Keywords |
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