An Integrated Statistical Method to Generate Potential Future Climate Scenarios to Analyse Droughts

被引:34
作者
Collados-Lara, Antonio-Juan [1 ]
Pulido-Velazquez, David [1 ,3 ]
Pardo-Iguzquiza, Eulogio [2 ]
机构
[1] Inst Geol & Minero Espana, Dept Invest Recursos Geol, 4 Edificio Zulema Bajo, Granada 18006, Spain
[2] Inst Geol & Minero Espana, Dept Invest Recursos Geol, Rios Rosas 23, Madrid 28003, Spain
[3] Univ Catolica Murcia, Dept Ingn Civil, Campus Jeronimos S-N, Murcia 30107, Spain
基金
欧盟地平线“2020”;
关键词
climate change; droughts analysis; statistical corrections; multi-objective analysis; ensemble of scenarios; Alto Genil catchment; BIAS CORRECTION; DAILY PRECIPITATION; DOWNSCALING METHODS; EUROPEAN DROUGHT; WATER SCARCITY; CHANGE IMPACTS; MODEL; SIMULATIONS; VARIABILITY; INDEXES;
D O I
10.3390/w10091224
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The 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.
引用
收藏
页数:24
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