DOI: 10.1002/joc.5441
论文题名: Evaluation of CMIP5 retrospective simulations of temperature and precipitation in northeastern Argentina
作者: Lovino M.A. ; Müller O.V. ; Berbery E.H. ; Müller G.V.
刊名: International Journal of Climatology
ISSN: 8998418
出版年: 2018
卷: 38 起始页码: e1158
结束页码: e1175
语种: 英语
英文关键词: Coupled Model Intercomparison Project Phase 5 (CMIP5)
; decadal simulations
; global climate models
; long-term simulations
; precipitation
; temperature
Scopus关键词: Atmospheric composition
; Climate change
; Correlation methods
; Land use
; Precipitation (chemical)
; Precipitation (meteorology)
; Systematic errors
; Temperature
; Annual precipitation
; Coupled Model Intercomparison Project
; Decadal simulations
; Evaluation metrics
; Global climate model
; Individual models
; Long term simulation
; Pearson correlation coefficients
; Climate models
; air temperature
; climate forcing
; climate modeling
; CMIP
; decadal variation
; ensemble forecasting
; extreme event
; global climate
; precipitation (climatology)
; rainfall
; Argentina
英文摘要: It is generally agreed that models that better simulate historical and current features of climate should also be the ones that more reliably simulate future climate. This article describes the ability of a selection of global climate models (GCMs) of the Coupled Model Intercomparison Project Phase 5 (CMIP5) to represent the historical and current mean climate and its variability over northeastern Argentina, a region that exhibits frequent extreme events. Two types of simulations are considered: Long-term simulations for 1901–2005 in which the models respond to climate forcing (e.g. changes in atmospheric composition and land use) and decadal simulations for 1961–2010 that are initialized from observed climate states. Monthly simulations of precipitation and temperature are statistically evaluated for individual models and their ensembles. Subsets of models that best represent the region's climate are further examined. First, models that have a Nash–Sutcliffe efficiency of at least 0.8 are taken as a subset that best represents the observed temperature fields and the mean annual cycle. Their temperature time series are in phase with observations (r > 0.92), despite systematic errors that if desired can be corrected by statistical methods. Likewise, models that have a precipitation Pearson correlation coefficient of at least 0.6 are considered that best represent regional precipitation features. GCMs are able to reproduce the annual precipitation cycle, although they underestimate precipitation amounts during the austral warm season (September through April) and slightly overestimate the cold season rainfall amounts. The ensembles for the subsets of models achieve the best evaluation metrics, exceeding the performance of the overall ensembles as well as those of the individual models. © 2018 The Authors. International Journal of Climatology published by John Wiley & Sons Ltd on behalf of the Royal Meteorological Society. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/116959
Appears in Collections: 气候减缓与适应
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作者单位: Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Centro de Estudios de Variabilidad y Cambio Climático (CEVARCAM), Universidad Nacional del Litoral, Facultad de Ingeniería y Ciencias Hídricas, Santa Fe, Argentina; Earth System Science Interdisciplinary Center/Cooperative Institute for Climate and Satellites-Maryland, University of Maryland, College Park, MD, United States
Recommended Citation:
Lovino M.A.,Müller O.V.,Berbery E.H.,et al. Evaluation of CMIP5 retrospective simulations of temperature and precipitation in northeastern Argentina[J]. International Journal of Climatology,2018-01-01,38