DOI: 10.1007/s10584-016-1683-4
Scopus记录号: 2-s2.0-84966344965
论文题名: Towards a fair comparison of statistical and dynamical downscaling in the framework of the EURO-CORDEX initiative
作者: Casanueva A. ; Herrera S. ; Fernández J. ; Gutiérrez J.M.
刊名: Climatic Change
ISSN: 0165-0009
EISSN: 1573-1480
出版年: 2016
卷: 137, 期: 2018-03-04 起始页码: 411
结束页码: 426
语种: 英语
英文关键词: EURO-CORDEX
; Precipitation indices
; Regional Climate Models
; Statistical downscaling
Scopus关键词: Climate change
; Linear transformations
; Mathematical transformations
; Climate change impact
; EURO-CORDEX
; Generalized linear model
; Global circulation model
; Precipitation indices
; Regional climate models
; Statistical downscaling
; Well-established techniques
; Climate models
; calibration
; climate change
; climate effect
; climate modeling
; data set
; downscaling
; general circulation model
; performance assessment
; precipitation assessment
; regional climate
; statistical analysis
; Spain
英文摘要: Both statistical and dynamical downscaling methods are well established techniques to bridge the gap between the coarse information produced by global circulation models and the regional-to-local scales required by the climate change Impacts, Adaptation, and Vulnerability (IAV) communities. A number of studies have analyzed the relative merits of each technique by inter-comparing their performance in reproducing the observed climate, as given by a number of climatic indices (e.g. mean values, percentiles, spells). However, in this paper we stress that fair comparisons should be based on indices that are not affected by the calibration towards the observed climate used for some of the methods. We focus on precipitation (over continental Spain) and consider the output of eight Regional Climate Models (RCMs) from the EURO-CORDEX initiative at 0.44∘ resolution and five Statistical Downscaling Methods (SDMs) —analog resampling, weather typing and generalized linear models— trained using the Spain044 observational gridded dataset on exactly the same RCM grid. The performance of these models is inter-compared in terms of several standard indices —mean precipitation, 90th percentile on wet days, maximum precipitation amount and maximum number of consecutive dry days— taking into account the parameters involved in the SDM training phase. It is shown, that not only the directly affected indices should be carefully analyzed, but also those indirectly influenced (e.g. percentile-based indices for precipitation) which are more difficult to identify. We also analyze how simple transformations (e.g. linear scaling) could be applied to the outputs of the uncalibrated methods in order to put SDMs and RCMs on equal footing, and thus perform a fairer comparison. © 2016, 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/84250
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. Departamento Matemática Aplicada y Ciencias de la Computación, Universidad de Cantabria, Avda. de los Castros, Santander, Spain; Grupo de Meteorología. Instituto de Física de Cantabria, CSIC-Universidad de Cantabria, Avda. de los Castros, Santander, Spain
Recommended Citation:
Casanueva A.,Herrera S.,Fernández J.,et al. Towards a fair comparison of statistical and dynamical downscaling in the framework of the EURO-CORDEX initiative[J]. Climatic Change,2016-01-01,137(2018-03-04)