An Integrated Statistical Method to Generate Potential Future Climate Scenarios to Analyse Droughts
AbstractThe objective of this paper is to investigate different methods to generate future potential climatic scenarios at monthly scale considering meteorological droughts. We assume that more reliable scenarios would be generated by using regional climatic models (RCMs) and statistical correction techniques that produce better approximations to the historical basic and drought statistics. A multi-objective analysis is proposed to identify the inferior approaches. Different ensembles (equifeasible and non-equifeasible) solutions are analysed, identifying their pros and cons. A sensitivity analysis of the method to spatial scale is also performed. The proposed methodology is applied in an alpine basin, the Alto Genil (southern Spain). The method requires historical climatic information and simulations provided by multiple RCMs (9 RCMs are considered in the proposed application) for a future period, assuming a potential emission scenario. We generate future series by applying two conceptual approaches, bias correction and delta change, using five statistical transformation techniques for each. The application shows that the method allows improvement of the definition of local climate scenarios from the RCM simulation considering drought statistics. The sensitivity of the results to the applied approach is analysed. View Full-Text
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Collados-Lara, A.-J.; Pulido-Velazquez, D.; Pardo-Igúzquiza, E. An Integrated Statistical Method to Generate Potential Future Climate Scenarios to Analyse Droughts. Water 2018, 10, 1224.
Collados-Lara A-J, Pulido-Velazquez D, Pardo-Igúzquiza E. An Integrated Statistical Method to Generate Potential Future Climate Scenarios to Analyse Droughts. Water. 2018; 10(9):1224.Chicago/Turabian Style
Collados-Lara, Antonio-Juan; Pulido-Velazquez, David; Pardo-Igúzquiza, Eulogio. 2018. "An Integrated Statistical Method to Generate Potential Future Climate Scenarios to Analyse Droughts." Water 10, no. 9: 1224.
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