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| Titel |
An objective determination of optimal site locations for detecting expected trends in upper-air temperature and total column ozone |
| VerfasserIn |
K. Kreher, G. E. Bodeker, M. Sigmond |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7316
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| Digitales Dokument |
URL |
| Erschienen |
In: Atmospheric Chemistry and Physics ; 15, no. 13 ; Nr. 15, no. 13 (2015-07-14), S.7653-7665 |
| Datensatznummer |
250119893
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| Publikation (Nr.) |
 copernicus.org/acp-15-7653-2015.pdf |
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| Zusammenfassung |
Detection of climate change requires a network of stable ground-based
long-term measurements. Building upon earlier work, we first explore
requirements of such measurements (such as maximum random uncertainty and
sampling frequency) to ensure a minimum random uncertainty in monthly mean
temperatures and to ensure effective detection of trends. In agreement with
previous work we find that only for individual measurement random
uncertainties > 0.2 K does the measurement random uncertainty start to
contribute significantly to the random uncertainty in the monthly mean.
For trend analysis, we find that the quality of the trend
determination is only compromised when the measurement random uncertainty
exceeds 2 K and measurements are made just once or twice a month.
In the second part of the study we provide guidance on how to most
effectively design a measurement network. To this end we developed a method
to objectively identify the optimal location of sites for detecting
projected trends in upper-air temperatures and total column ozone in the
shortest possible time. This is done by first estimating the spatial distribution
of the minimum length of time during which measurements have
to be made in order to detect projected trends in temperature
and ozone. This quantity is calculated from the
unforced variance in the signal and the degree of autocorrelation, both
estimated from historical data sets and assumed not to change in the future,
and the projected trends as estimated from chemistry–climate models. The
optimal site locations are then selected by an iterative procedure based on
the minimum time required to detect a trend and a minimal distance between
different measurement sites. While the optimal sites identified here result
from our use of only one of a wide range of objective strategies, these
results provide additional incentives for initiating measurement programmes
at these sites or, if already in operation, to continue to be supported. |
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