DOI: 10.1007/s10584-015-1582-0
Scopus记录号: 2-s2.0-84961155229
论文题名: Selecting climate simulations for impact studies based on multivariate patterns of climate change
作者: Mendlik T. ; Gobiet A.
刊名: Climatic Change
ISSN: 0165-0009
EISSN: 1573-1480
出版年: 2016
卷: 135, 期: 2018-03-04 起始页码: 381
结束页码: 393
语种: 英语
Scopus关键词: Climate models
; Cluster analysis
; Principal component analysis
; Climate change impact
; Computational costs
; Essential characteristic
; Meteorological input
; Meteorological parameters
; Multi-model ensemble
; Multivariate patterns
; Temperature and humidities
; Climate change
; climate change
; climate modeling
; cluster analysis
; computer simulation
; ensemble forecasting
; humidity
; multivariate analysis
; principal component analysis
; sampling
; temperature
英文摘要: In climate change impact research it is crucial to carefully select the meteorological input for impact models. We present a method for model selection that enables the user to shrink the ensemble to a few representative members, conserving the model spread and accounting for model similarity. This is done in three steps: First, using principal component analysis for a multitude of meteorological parameters, to find common patterns of climate change within the multi-model ensemble. Second, detecting model similarities with regard to these multivariate patterns using cluster analysis. And third, sampling models from each cluster, to generate a subset of representative simulations. We present an application based on the ENSEMBLES regional multi-model ensemble with the aim to provide input for a variety of climate impact studies. We find that the two most dominant patterns of climate change relate to temperature and humidity patterns. The ensemble can be reduced from 25 to 5 simulations while still maintaining its essential characteristics. Having such a representative subset of simulations reduces computational costs for climate impact modeling and enhances the quality of the ensemble at the same time, as it prevents double-counting of dependent simulations that would lead to biased statistics. © 2015, The Author(s). Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/84346
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: Wegener Center for Climate and Global Change, University of Graz, Brandhofgasse 5, Graz, Austria
Recommended Citation:
Mendlik T.,Gobiet A.. Selecting climate simulations for impact studies based on multivariate patterns of climate change[J]. Climatic Change,2016-01-01,135(2018-03-04)