期刊
NATURE CLIMATE CHANGE
卷 3, 期 5, 页码 502-507出版社
NATURE PUBLISHING GROUP
DOI: 10.1038/NCLIMATE1834
关键词
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资金
- NOAA (Oceans and Human Health Initiative) [NA08NOS4730321]
- Graham Environmental Sustainability Institute (GESI) at the University of Michigan
- NSF [ATM-0830068]
- NOAA [NA09OAR4310058]
- NASA [NNX09AN50G]
- QweCI EUFP7 project
- National Science Foundation
- ICREA Funding Source: Custom
The existence of predictability in the climate system beyond the relatively short timescales of synoptic weather(1,2) has provided significant impetus to investigate climate variability and its consequences for society. In particular, relationships between the relatively slow changes in sea surface temperature (SST) and climate variability at widely removed points across the globe provide a basis for statistical and dynamical efforts to predict numerous phenomena, from rainfall to disease incidence, at seasonal to decadal timescales. We describe here a remote influence, identified through observational analysis and supported through numerical experiments with a coupled atmosphere-ocean model, of the tropical South Atlantic (TSA) on both monsoon rainfall and malaria epidemics in arid northwest India. Moreover, SST in the TSA is shown to provide the basis for an early warning of anomalous hydrological conditions conducive to malaria epidemics four months later, therefore at longer lead times than those afforded by rainfall. We find that the TSA is not only significant as a modulator of the relationship between the monsoon and the El Nino/Southern Oscillation, as has been suggested by previous work(3,4), but for certain regions and temporal lags is in fact a dominant driver of rainfall variability and hence malaria outbreaks.
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