We found a match
Your institution may have rights to this item. Sign in to continue.
- Title
Forecasting terrestrial water storage changes in the Amazon Basin using Atlantic and Pacific sea surface temperatures.
- Authors
de Linage, C.; Famiglietti, J. S.; Randerson, J. T.
- Abstract
Floods and droughts frequently affect the Amazon River basin, impacting transportation, river navigation, agriculture, and ecosystem processes within several South American countries. Here we examined how sea surface temperatures (SSTs) influence in-terannual variability of terrestrial water storage anomalies (TWSAs) in different regions within the Amazon basin and propose a modeling framework for inter-seasonal flood and drought forecasting. Three simple statistical models forced by a linear combination of lagged spatial averages of central Pacific (Niño 4 index) and tropical North Atlantic (TNAI index) SSTs 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 regions, and 43 % for the Amazon basin as a whole with a 3 month lead time between the SST indices and TWSAs. Model performance varied seasonally: it was higher than average during the rainfall wet season in the northeastern Amazon and during the dry season in the central and western regions. The predictive capability of the combined model was degraded with increasing lead times. Degradation was smaller in the northeastern Amazon (where 49% of the variance was explained using an 8 month lead time vs. 69% for a 1 month lead time) compared to the central and western Amazon (where 22 % of the variance was explained at 8 months vs. 43 % at 1 month). These relationships may enable the development of an early warning system for flood and drought risk. This work also strengthens our understanding of the mechanisms regulating interannual variability in Amazon fires, as water storage deficits may subsequently lead to decreases in transpiration and atmospheric water vapor that cause more severe fire weather.
- Subjects
AMAZON River Watershed; FLOOD forecasting; DROUGHT forecasting; WATER storage; BALLISTIC missile early warning system; OCEAN temperature; ATMOSPHERIC models
- Publication
Hydrology & Earth System Sciences Discussions, 2013, Vol 10, Issue 10, p12453
- ISSN
1812-2108
- Publication type
Article
- DOI
10.5194/hessd-10-12453-2013