DOI: 10.1175/JCLI-D-11-00199.1
Scopus记录号: 2-s2.0-84862108523
论文题名: A scaling approach to probabilistic assessment of regional climate change
作者: Frieler K. ; Meinshausen M. ; Mengel M. ; Braun N. ; Hare W.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2012
卷: 25, 期: 9 起始页码: 3117
结束页码: 3144
语种: 英语
Scopus关键词: Black carbon emission
; Climate prediction
; Ensembles
; Forcings
; Global-mean temperature
; Greenland Ice Sheet
; Linear relationships
; Linear scaling
; Model output statistics
; Ocean general circulation models
; Online database
; Precipitation change
; Probabilistic assessments
; Probabilistic projections
; Quasi-linear
; Regional climate changes
; Regional effects
; Scaling coefficients
; Scaling relationships
; Statistical techniques
; Surface mass balance
; Uncertainty distributions
; Glacial geology
; Greenhouse gases
; Precipitation (chemical)
; Regression analysis
; Sensitivity analysis
; Climate change
; climate change
; climate prediction
; ensemble forecasting
; mass balance
; precipitation (climatology)
; probability
; regional climate
; regression analysis
; temperature effect
; Arctic
; Greenland
; Greenland Ice Sheet
英文摘要: A new approach to probabilistic projections of regional climate change is introduced. It builds on the already established quasi-linear relation between global-mean temperature and regional climate change found in atmosphere- ocean general circulation models (AOGCMs). The new approach simultaneously 1) takes correlations between temperature- and precipitation-related uncertainty distributions into account, 2) enables the inclusion of predictors other than global-mean temperature, and 3) checks for the interscenario and interrun variability of the scaling relationships. This study tests the effectiveness of SO x and black carbon emissions and greenhouse gas forcings as additional predictors of precipitation changes. The future precipitation response is found to deviate substantially from the linear relationship with global-mean temperature change in some regions; thereby, the twomain limitations of a simple linear scaling approach, namely having to rely on exogenous aerosol experiments (or ignoring their regional effect), and ignoring changes in scaling coefficients when approaching equilibriumconditions, are addressed. The additional predictors canmarkedly improve the emulation of AOGCM simulations. In some regions, variations in hydrological sensitivity (the percentage change of precipitation per degree of warming) across different scenarios can be reduced by more than 50%. Coupled to probabilistic projections of global-mean temperatures and greenhouse gas forcings, bidimensional distributions of regional temperature and precipitation changes accounting formultiple uncertainties are derived. Based on 20 Fourth Assessment Report AOGCMs (AR4 AOGCMs), probabilistic projections are provided for two representative concentration pathway (RCP) scenarios and 31 world regions (online database at www.pik-potsdam. de/primap/regional_temp_and_precip).As an example application of the projections for climate adaptation and vulnerability studies, future changes in the surface mass balance of the Greenland Ice Sheet are computed. © 2012 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/52424
Appears in Collections: 气候变化事实与影响
There are no files associated with this item.
作者单位: School of Earth Sciences, University of Melbourne, Melbourne, VIC, Australia; Ecofys, Cologne, Germany; Climate Analytics, Potsdam, Germany; School of Earth Sciences, University of Melbourne, Melbourne, VIC, Australia
Recommended Citation:
Frieler K.,Meinshausen M.,Mengel M.,et al. A scaling approach to probabilistic assessment of regional climate change[J]. Journal of Climate,2012-01-01,25(9)