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| Titel |
Temporal and spatial scaling impacts on extreme precipitation |
| VerfasserIn |
B. Eggert, P. Berg, J. O. Haerter, D. Jacob, C. Moseley |
| 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. 10 ; Nr. 15, no. 10 (2015-05-29), S.5957-5971 |
| Datensatznummer |
250119766
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| Publikation (Nr.) |
 copernicus.org/acp-15-5957-2015.pdf |
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| Zusammenfassung |
| Convective and stratiform precipitation events have fundamentally different
physical causes. Using a radar composite over Germany, this study separates
these precipitation types and compares extremes at different spatial and
temporal scales, ranging from 1 to 50 km and 5 min to 6 h, respectively.
Four main objectives are addressed. First, we investigate extreme
precipitation intensities for convective and stratiform precipitation events
at different spatial and temporal resolutions to identify type-dependent
space and time reduction factors and to analyze regional and seasonal
differences over Germany. We find strong differences between the types, with
up to 30% higher reduction factors for convective compared to stratiform
extremes, exceeding all other observed seasonal and regional differences
within one type. Second, we investigate how the differences in reduction
factors affect the contribution of each type to extreme events as a whole,
again dependent on the scale and the threshold chosen. A clear shift occurs
towards more convective extremes at higher resolution or higher percentiles.
For horizontal resolutions of current climate model simulations,
i.e., ~10 km, the temporal resolution of the data as well as the
chosen threshold have profound influence on which type of extreme will be
statistically dominant. Third, we compare the ratio of area to duration
reduction factor for convective and stratiform events and find that
convective events have lower effective advection velocities than stratiform
events and are therefore more strongly affected by spatial than by temporal
aggregation. Finally, we discuss the entire precipitation distribution
regarding data aggregation and identify matching pairs of temporal and
spatial resolutions where similar distributions are observed. The information
is useful for planning observational networks or storing model data at
different temporal and spatial scales. |
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