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| Titel |
Non-linear statistical downscaling of present and LGM precipitation and temperatures over Europe |
| VerfasserIn |
M. Vrac, P. Marbaix, D. Paillard, P. Naveau |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1814-9324
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| Digitales Dokument |
URL |
| Erschienen |
In: Climate of the Past ; 3, no. 4 ; Nr. 3, no. 4 (2007-12-19), S.669-682 |
| Datensatznummer |
250001181
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| Publikation (Nr.) |
 copernicus.org/cp-3-669-2007.pdf |
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| Zusammenfassung |
Local-scale climate information is increasingly needed for the study of past,
present and future climate changes. In this study we develop a non-linear
statistical downscaling method to generate local temperatures and
precipitation values from large-scale variables of a Earth System Model of
Intermediate Complexity (here CLIMBER). Our statistical downscaling scheme is
based on the concept of Generalized Additive Models (GAMs), capturing
non-linearities via non-parametric techniques. Our GAMs are calibrated on the
present Western Europe climate. For this region, annual GAMs (i.e. models
based on 12 monthly values per location) are fitted by combining two types of
large-scale explanatory variables: geographical (e.g. topographical
information) and physical (i.e. entirely simulated by the CLIMBER model).
To evaluate the adequacy of the non-linear transfer functions fitted on the
present Western European climate, they are applied to different spatial and
temporal large-scale conditions. Local projections for present North America
and Northern Europe climates are obtained and compared to local observations.
This partially addresses the issue of spatial robustness of our transfer
functions by answering the question "does our statistical model remain valid
when applied to large-scale climate conditions from a region different from
the one used for calibration?". To asses their temporal performances, local
projections for the Last Glacial Maximum period are derived and compared to
local reconstructions and General Circulation Model outputs.
Our downscaling methodology performs adequately for the Western Europe
climate. Concerning the spatial and temporal evaluations, it does not behave
as well for Northern America and Northern Europe climates because the
calibration domain may be too different from the targeted regions. The
physical explanatory variables alone are not capable of downscaling realistic
values. However, the inclusion of geographical-type variables – such as
altitude, advective continentality and moutains effect on wind (W–slope) –
as GAM explanatory variables clearly improves our local projections. |
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