Computer Science – Performance
Scientific paper
Jan 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009georl..3602706c&link_type=abstract
Geophysical Research Letters, Volume 36, Issue 2, CiteID L02706
Computer Science
Performance
1
Global Change: Climate Variability (1635, 3305, 3309, 4215, 4513), Global Change: Global Climate Models (3337, 4928), Atmospheric Processes: General Circulation (1223)
Scientific paper
While General Circulation Models (GCM) generally converge well at the global level, results for individual regions usually show a wide range of variation. This study assesses the performance of seventeen GCMs regarding their simulation of temperature and precipitation based on hindcasts for the periods of 1961-1990 and 1931-1960. Skill scores are plotted on a 2° × 2° grid to present ``zones'' of GCM performance. An overlay of these skill score maps with global climate zones, land cover, and elevation maps shows correlations between GCM performance and the distribution of these geographic variables. No GCM is superior in predicting temperature or precipitation for the whole world, although some GCMs score better in particular regions. For researchers working with GCM results and policymakers who need to make decisions based on GCM projections, the skill score maps may provide useful guidance; while for GCM developers, the skill score maps may open areas for further study to improve their models.
Cai Ximing
Ringler Claudia
Wang Dingbao
Zhu Tingju
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