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| Titel |
Statistical prediction of terrestrial water storage changes in the Amazon Basin using tropical Pacific and North Atlantic sea surface temperature anomalies |
| VerfasserIn |
C. De Linage, J. S. Famiglietti, J. T. Randerson |
| 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 ; 18, no. 6 ; Nr. 18, no. 6 (2014-06-04), S.2089-2102 |
| Datensatznummer |
250120377
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| Publikation (Nr.) |
 copernicus.org/hess-18-2089-2014.pdf |
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| Zusammenfassung |
| Floods and droughts frequently affect the Amazon River basin, impacting
transportation, agriculture, and ecosystem processes within several South
American countries. Here we examine how sea surface temperature (SST)
anomalies influence interannual variability of terrestrial water storage
anomalies (TWSAs) in different regions within the Amazon Basin and propose a
statistical modeling framework for TWSA prediction on seasonal timescales.
Three simple semi-empirical models forced by a linear combination of lagged
spatial averages of central Pacific and tropical North Atlantic climate
indices (Niño 4 and TNAI) were calibrated against a decade-long record of
3°, monthly TWSAs observed by the Gravity Recovery And Climate
Experiment (GRACE) satellite mission. Niño 4 was the primary external
forcing in the northeastern region of the Amazon Basin, whereas TNAI was
dominant in central and western regions. A combined model using the two
indices improved the fit significantly (p < 0.05) for at least 64%
of the grid cells within the basin, compared to models forced solely with
Niño 4 or TNAI. The combined model explained 66% of the observed
variance in the northeastern region, 39% in the central and western
region, and 43% for the Amazon Basin as a whole, with a 3-month lead time
between the climate indices and the predicted TWSAs. Model performance varied
seasonally: it was higher than average during the wet season in the
northeastern Amazon and during the dry season in the central and western
region. The predictive capability of the combined model was degraded with
increasing lead times. Degradation rates were lower in the northeastern
Amazon (where 49% of the variance was explained using an 8-month lead time
versus 69% for a 1-month lead time) compared to the central and western
Amazon (where 22% of the variance was explained at 8 months versus 43%
at 1 month). These relationships may contribute to an improved understanding
of the climate processes regulating the spatial patterns of flood and drought
risk in South America. |
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