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| Titel |
Assessment of precipitation and temperature data from CMIP3 global climate models for hydrologic simulation |
| VerfasserIn |
T. A. McMahon, M. C. Peel, D. J. Karoly |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1027-5606
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| Digitales Dokument |
URL |
| Erschienen |
In: Hydrology and Earth System Sciences ; 19, no. 1 ; Nr. 19, no. 1 (2015-01-21), S.361-377 |
| Datensatznummer |
250120597
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| Publikation (Nr.) |
 copernicus.org/hess-19-361-2015.pdf |
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| Zusammenfassung |
| The objective of this paper is to identify better performing Coupled Model Intercomparison Project phase 3 (CMIP3) global
climate models (GCMs) that reproduce grid-scale climatological statistics of
observed precipitation and temperature for input to hydrologic simulation
over global land regions. Current assessments are aimed mainly at examining
the performance of GCMs from a climatology perspective and not from a
hydrology standpoint. The performance of each GCM in reproducing the
precipitation and temperature statistics was ranked and better performing
GCMs identified for later analyses. Observed global land surface
precipitation and temperature data were drawn from the Climatic Research Unit (CRU) 3.10 gridded
data set and re-sampled to the resolution of each GCM for comparison.
Observed and GCM-based estimates of mean and standard deviation of annual
precipitation, mean annual temperature, mean monthly precipitation and
temperature and Köppen–Geiger climate type were compared. The main
metrics for assessing GCM performance were the Nash–Sutcliffe efficiency
(NSE) index and root mean square error (RMSE) between modelled and observed long-term statistics. This
information combined with a literature review of the performance of the
CMIP3 models identified the following better performing GCMs from a
hydrologic perspective: HadCM3 (Hadley Centre for Climate Prediction and
Research), MIROCm (Model for Interdisciplinary Research on Climate) (Center for Climate System Research (The University of
Tokyo), National Institute for Environmental Studies, and Frontier Research
Center for Global Change), MIUB (Meteorological Institute of the University
of Bonn, Meteorological Research Institute of KMA, and Model and Data
group), MPI (Max Planck Institute for Meteorology) and MRI (Japan
Meteorological Research Institute). The future response of these GCMs was
found to be representative of the 44 GCM ensemble members which confirms
that the selected GCMs are reasonably representative of the range of future
GCM projections. |
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