Prediction Accuracy;
Lead Time;
Discount Factor;
Internal Variability;
Climate Prediction;
D O I:
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摘要:
The role of short- and long-term climate predictions in determining the success of adaptation to climate change is investigated. A simple theoretical model that captures the relationship between adaptive performance, decision structure, and prediction accuracy at different temporal scales is developed, and its implications deduced. It is shown that users who face high adjustment costs (i.e. are inflexible) depend more heavily on accurate long-term predictions than those who are able to adjust their adaptation strategies at low cost. However, the constraints on the accuracy of long-term predictions in order for them to be ‘accurate enough’ to be recommended unreservedly are strongest for precisely those users who desire them most. There are thus intrinsic structural limitations to the utility of long-term predictions for adaptive decision making. In addition, the heterogeneous dependence of adaptive performance on predictions at different temporal scales gives rise to a resource allocation problem for investments aimed at improving predictions so as to maximize their social benefits. It is suggested that an explicit distributional framework that matches users’ needs with scientific feasibility is needed in order to guide such investments, and key issues any such framework will need to address are discussed.
机构:
Ctr Int Forestry Res, Jakarta 10065, IndonesiaCtr Int Forestry Res, Jakarta 10065, Indonesia
Guariguata, Manuel R.
Cornelius, Jonathan P.
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机构:
James Cook Univ, Sch Marine & Trop Biol, Agroforestry & Novel Crops Unit, Cairns, Qld 4870, AustraliaCtr Int Forestry Res, Jakarta 10065, Indonesia
Cornelius, Jonathan P.
Locatelli, Bruno
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机构:
CIRAD UPR Forest Resources, Montpellier, France
CATIE, Global Change Grp, Turrialba 7170, Costa RicaCtr Int Forestry Res, Jakarta 10065, Indonesia
Locatelli, Bruno
Forner, Claudio
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h-index: 0
机构:
Secretariat United Nations Framework Convent Clim, D-53175 Bonn, GermanyCtr Int Forestry Res, Jakarta 10065, Indonesia
Forner, Claudio
Sanchez-Azofeifa, G. Arturo
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h-index: 0
机构:
Univ Alberta, Dept Earth & Atmospher Sci, Edmonton, AB T6G 2E3, CanadaCtr Int Forestry Res, Jakarta 10065, Indonesia