DOI: 10.1175/JCLI-D-17-0780.1
Scopus记录号: 2-s2.0-85049755326
论文题名: Performance of pattern-scaled climate projections under high-end warming. Part I: Surface air temperature over land
作者: Osborn T.J. ; Wallace C.J. ; Lowea J.A. ; Bernie D.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2018
卷: 31, 期: 14 起始页码: 5667
结束页码: 5680
语种: 英语
英文关键词: Anthropogenic effects
; Climate change
; Climate models
; Statistical techniques
; Temperature
Scopus关键词: Climate change
; Errors
; Global warming
; Mean square error
; Temperature
; Anthropogenic effects
; Climate change impact
; Climate change projections
; General circulation model
; Initial condition ensembles
; Root mean square errors
; Statistical techniques
; Surface air temperatures
; Climate models
; air temperature
; anthropogenic effect
; climate change
; climate modeling
; global warming
; statistical analysis
英文摘要: Pattern scaling is widely used to create climate change projections to investigate future impacts. We consider the performance of pattern scaling for emulating the HadGEM2-ES general circulation model (GCM) paying particular attention to "high end" warming scenarios and to different choices of GCM simulations used to diagnose the climate change patterns. We demonstrate that evaluating pattern-scaling projections by comparing them with GCM simulations containing unforced variability gives a significantly less favorable view of the actual performance of pattern scaling. Using a four-member initial-condition ensemble of HadGEM2-ES simulations, we infer that the root-mean-square errors of pattern-scaled monthly temperature changes over land are less than 0.25°C for global warming up to approximately 3.5°C. Some regional errors are larger than this and, for this GCM, there is a tendency for pattern scaling to underestimate warming over land. For warming above 3.5°C, the pattern-scaled projection errors grow but remain small relative to the climate change signal. We investigate whether patterns diagnosed by pooling GCM experiments from several scenarios are suitable for emulating the GCM under a high-end warming scenario. For global warming up to 3.5°C, pattern scaling using this pooled pattern closely emulates GCM simulations. For warming beyond 3.5°C, pattern-scaling performance is notably improved by using patterns diagnosed only from the high-forcing representative concentration pathway 8.5 (RCP8.5) scenario. Assessments of climate change impacts under high-end warming using pattern-scaling projections could be improved by using change patterns diagnosed from pooled scenarios for projections up to 3.5°C above preindustrial levels and patterns diagnosed from only strong forcing simulations for projecting beyond that. Similar findings are obtained for five other GCMs. © 2018 American Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/111488
Appears in Collections: 气候减缓与适应
There are no files associated with this item.
作者单位: Climatic Research Unit, School of Environmental Sciences, University of East Anglia, Norwich, United Kingdom; Met Office Hadley Centre, Exeter, United Kingdom; Priestley Centre, University of Leeds, Leeds, United Kingdom
Recommended Citation:
Osborn T.J.,Wallace C.J.,Lowea J.A.,et al. Performance of pattern-scaled climate projections under high-end warming. Part I: Surface air temperature over land[J]. Journal of Climate,2018-01-01,31(14)