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| Titel |
Comparison results for the CFSv2 hindcasts and statistical downscaling over the northeast of Brazil |
| VerfasserIn |
G. A. M. Silva, D. Mendes |
| Medientyp |
Artikel
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| Sprache |
Englisch
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| ISSN |
1680-7340
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| Digitales Dokument |
URL |
| Erschienen |
In: 8th EGU Alexander von Humboldt Conference "Natural Disasters, Global Change, and the Preservation of World Heritage Sites" ; Nr. 35 (2013-07-25), S.79-88 |
| Datensatznummer |
250019101
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| Publikation (Nr.) |
 copernicus.org/adgeo-35-79-2013.pdf |
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| Zusammenfassung |
| An Artificial Neural Networks (ANNs) approach was used to reproduce the
precipitation anomalies for the rainy seasons over the south and north parts
of the Northeast of Brazil (NEB) during 1982–2009 period. The seasonal
hindcasts of precipitation anomalies from Climate Forecast System v2 (CFSv2)
model and the observed dominant modes of anomalous Sea Surface Temperature
over the South and North Atlantic Ocean were used as explanatory variables
separately. The reduction of dispersion between the explanatory and
dependent variables after the fit of the networks suggest the ANN as an
important complementary technique for the climate studies over the NEB.
However, a large dataset are required to the models capture the non-linear
process in more details. The practical implication of the results is that
ANNs constructed here could be applied in further analyses, for example, to
explore the ANN's ability in improving the seasonal climate forecasts
considering that the numerical and statistical methods must be complementary
tools. |
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