 |
| Titel |
Building long-term and high spatio-temporal resolution precipitation and air temperature reanalyses by mixing local observations and global atmospheric reanalyses: the ANATEM model |
| VerfasserIn |
A. Kuentz, T. Mathevet, J. Gailhard, B. Hingray |
| Medientyp |
Artikel
|
| Sprache |
Englisch
|
| ISSN |
1027-5606
|
| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 19, no. 6 ; Nr. 19, no. 6 (2015-06-15), S.2717-2736 |
| Datensatznummer |
250120738
|
| Publikation (Nr.) |
 copernicus.org/hess-19-2717-2015.pdf |
|
|
|
|
|
| Zusammenfassung |
Efforts to improve the understanding of past climatic or hydrologic
variability have received a great deal of attention in various fields of
geosciences such as glaciology, dendrochronology, sedimentology and
hydrology. Based on different proxies, each research community produces
different kinds of climatic or hydrologic reanalyses at different
spatio-temporal scales and resolutions. When considering climate or
hydrology, many studies have been devoted to characterising variability,
trends or breaks using observed time series representing different regions or
climates of the world. However, in hydrology, these studies have usually been
limited to short temporal scales (mainly a few decades and more rarely a
century) because they require observed time series (which suffer from a
limited spatio-temporal density).
This paper introduces ANATEM, a method that combines local observations
and large-scale climatic information (such as the 20CR Reanalysis) to build
long-term probabilistic air temperature and precipitation time series with a high
spatio-temporal resolution (1 day and a few km2). ANATEM was tested on
the reconstruction of air temperature and precipitation time series of 22 watersheds situated
in the Durance River basin, in the French Alps. Based on a multi-criteria and
multi-scale diagnosis, the results show that ANATEM improves the performance
of classical statistical models – especially concerning spatial homogeneity –
while providing an original representation of uncertainties which are
conditioned by atmospheric circulation patterns.
The ANATEM model has been also evaluated for the regional scale against
independent long-term time series and was able to capture regional
low-frequency variability over more than a century (1883–2010). |
| |
|
| Teil von |
|
|
|
|
|
|
|
|