Observational constraints indicate risk of drying in the Amazon basin

Hideo Shiogama (), Seita Emori, Naota Hanasaki, Manabu Abe, Yuji Masutomi, Kiyoshi Takahashi and Toru Nozawa
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Hideo Shiogama: National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
Seita Emori: Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
Naota Hanasaki: National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
Manabu Abe: Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
Yuji Masutomi: Center for Environmental Science in Saitama, 914 Kamitanadare, Kazo, Saitama 347-0115, Japan.
Kiyoshi Takahashi: Center for Global Environmental Research, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.
Toru Nozawa: National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan.

Nature Communications, 2011, vol. 2, issue 1, 1-7

Abstract: Abstract Climate warming due to human activities will be accompanied by hydrological cycle changes. Economies, societies and ecosystems in South America are vulnerable to such water resource changes. Hence, water resource impact assessments for South America, and corresponding adaptation and mitigation policies, have attracted increased attention. However, substantial uncertainties remain in the current water resource assessments that are based on multiple coupled Atmosphere Ocean General Circulation models. This uncertainty varies from significant wetting to catastrophic drying. By applying a statistical method, we characterized the uncertainty and identified global-scale metrics for measuring the reliability of water resource assessments in South America. Here, we show that, although the ensemble mean assessment suggested wetting across most of South America, the observational constraints indicate a higher probability of drying in the Amazon basin. Thus, over-reliance on the consensus of models can lead to inappropriate decision making.

Date: 2011
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DOI: 10.1038/ncomms1252

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