DOI: 10.1007/s10584-014-1270-5
Scopus记录号: 2-s2.0-84911967787
论文题名: Statistical downscaling of climate impact indices: testing the direct approach
作者: Casanueva A. ; Frías M.D. ; Herrera S. ; San-Martín D. ; Zaninovic K. ; Gutiérrez J.M.
刊名: Climatic Change
ISSN: 0165-0009
EISSN: 1573-1480
出版年: 2014
卷: 127, 期: 2018-03-04 起始页码: 547
结束页码: 560
语种: 英语
Scopus关键词: Climate impacts
; Direct approach
; Statistical downscaling
; accuracy assessment
; downscaling
; humidity
; instrumentation
; nature-society relations
; numerical model
; precipitation (climatology)
; socioeconomic impact
; stakeholder
; statistical analysis
; temperature effect
; trade-off
; wind velocity
英文摘要: Climate Impact Indices (CIIs) are being increasingly used in different socioeconomic sectors to transfer information about climate change impacts to stakeholders. Typically, CIIs comprise into a single index several weather variables —such as temperature, wind speed, precipitation and humidity— which are relevant for a particular problem of interest. Moreover, most of the CIIs require daily (or monthly) physical coherence among these variables for their proper calculation. This constraints the number of statistical downscaling techniques suitable for a component-wise approach to this problem. We test the suitability of the alternative “direct” downscaling approach in which the downscaling method is applied directly to the CII, thus circumventing the multi-variable problem and allowing the use of a wider range of downscaling methods. For illustrative purposes, we consider two popular CIIs —the Fire Weather Index (FWI) and the Physiological Equivalent Temperature (PET), used in the wildfire and tourism sectors, respectively— and compare the performance of the two approaches using the analog method, a simple and popular method providing inter-variable dependence. The results obtained with ‘perfect’ reanalysis predictors are comparable for both approaches, although smaller accuracy is obtained in general with the direct approach. Moreover, similar climate change ‘deltas’ are obtained with both approaches when applied to an illustrative future global projection using the ECHAM5 model. Overall, there is a trade-off between performance and simplicity which needs to be balanced for each particular application. © 2014, Springer Science+Business Media Dordrecht. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/84821
Appears in Collections: 气候减缓与适应 气候变化事实与影响
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作者单位: Grupo de Meteorología, Dpto. Matemática Aplicada y Ciencias de la Computación, Univ. de Cantabria, Avda. de los Castros, s/n, Santander, Spain; Predictia Intelligent Data Solutions S.L., Avda. de los Castros, s/n, Santander, Spain; Meteorological and Hydrological Service of Croatia, Grič 3, Zagreb, Croatia; Grupo de Meteorología, Instituto de Física de Cantabria, CSIC-Univ. de Cantabria, Avda. de los Castros, s/n, Santander, Spain
Recommended Citation:
Casanueva A.,Frías M.D.,Herrera S.,et al. Statistical downscaling of climate impact indices: testing the direct approach[J]. Climatic Change,2014-01-01,127(2018-03-04)