DOI: 10.1002/joc.5193
论文题名: Use of observed temperature statistics in ranking CMIP5 model performance over the Western Himalayan Region of India
作者: Das L. ; Dutta M. ; Mezghani A. ; Benestad R.E.
刊名: International Journal of Climatology
ISSN: 8998418
出版年: 2018
卷: 38, 期: 2 起始页码: 554
结束页码: 570
语种: 英语
英文关键词: CMIP5
; ERA-interim
; GCMs
; MICE
; seasonal cycle
; spatial correlation
; trends
Scopus关键词: Climatology
; Earth atmosphere
; CMIP5
; Era interims
; GCMs
; MICE
; Seasonal cycle
; Spatial correlations
; Trends
; Climate models
; air temperature
; atmospheric general circulation model
; climate modeling
; CMIP
; cooling
; correlation
; ranking
; seasonal variation
; spatial analysis
; trend analysis
; warming
; Himalayas
; India
英文摘要: Assessing warming over the Western Himalayan Region (WHR) of India is challenging due to its limited station data availability and poor data quality. The missing values in the station data were replaced using the Multiple Imputation Chained Equation technique. Finally, 16 stations having continuous records during 1969–2009 were considered as the ‘reference stations’ for assessing the warming/cooling trends in addition to evaluate the Coupled Model Intercomparison, phase 5 (CMIP5), Global Circulation Model (GCM). Station data indicates winter (DJF) warming is higher and rapid (1.41 °C) than the other seasons and less warming was observed in the post-monsoon (0.31 °C) season. Overall mean annual warming over WHR is ∼0.84 °C during 1969–2009. The performance of 34 CMIP5 models was evaluated based on three different criteria namely (1) mean seasonal cycle, (2) temporal trends and (3) spatial correlation between simulated and observed signals for common available period of 1969–2003 over the study area. Models are provided a final rank on the basis of the cumulative rank obtained in each of three approaches. CMCC-CM, GISS-E2-H and MIROC 5 are three top-ranked models while MIROC-ESM, MIROC-ESM-CHEM and bcc-csm1-1 are three bottom-ranked models over the WHR. The study also extended to judge whether the selected top-ranked models perform well through two alternative data sources namely European Reanalysis (ERA)-interim and Climate Research Unit (CRU), which have not used in the process of model evaluation. The spatial patterns of top-ranked GCM are similar to the spatial pattern obtained through ERA-interim and CRU while zoomed in to WHR but bottom-ranked models fail to reproduce such spatial patterns indicating the top-ranked GCMs would offer more reliability for projecting future climate over WHR. © 2017 Royal Meteorological Society Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/117103
Appears in Collections: 气候减缓与适应
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作者单位: Department of Agricultural Meteorology and Physics, Bidhan Chandra Krishi Viswavidyalaya, Nadia, India; Division for Model and Climate Analysis, The Norwegian Meteorological Institute, Oslo, Norway
Recommended Citation:
Das L.,Dutta M.,Mezghani A.,et al. Use of observed temperature statistics in ranking CMIP5 model performance over the Western Himalayan Region of India[J]. International Journal of Climatology,2018-01-01,38(2)