DOI: 10.1175/JCLI-D-12-00259.1
Scopus记录号: 2-s2.0-84878955703
论文题名: Evaluation of temperature and precipitation trends and long-term persistence in CMIP5 twentieth-century climate simulations
作者: Kumar S. ; Merwade V. ; Kinter III J.L. ; Niyogi D.
刊名: Journal of Climate
ISSN: 8948755
出版年: 2013
卷: 26, 期: 12 起始页码: 4168
结束页码: 4185
语种: 英语
Scopus关键词: Coupled Model Intercomparison Project
; Global historical climatology network
; Non-parametric trends
; Precipitation trends
; Regional effects
; Relative performance
; Spatial variability
; Trends
; Climate change
; Data processing
; Time series
; Climate models
; air temperature
; climate change
; climate modeling
; Hadley cell
; hydrology
; precipitation (climatology)
; spatial variation
; time series
; trend analysis
; twentieth century
英文摘要: The authors have analyzed twentieth-century temperature and precipitation trends and long-term persistence from 19 climate models participating in phase 5 of the Coupled Model Intercomparison Project (CMIP5). This study is focused on continental areas (60°S-60°N) during 1930-2004 to ensure higher reliability in the observations. A nonparametric trend detection method is employed, and long-term persistence is quantified using the Hurst coefficient, taken from the hydrology literature. The authors found that the multimodel ensemble-mean global land-average temperature trend (0.07°C decade-1) captures the corresponding observed trend well (0.08°C decade-1). Globally, precipitation trends are distributed (spatially) at about zero in both the models and in the observations. There are large uncertainties in the simulation of regional-/local-scale temperature and precipitation trends. The models' relative performances are different for temperature and precipitation trends. The models capture the long-term persistence in temperature reasonably well. The areal coverage of observed long-term persistence in precipitation is 60% less (32% of land area) than that of temperature (78%). The models have limited capability to capture the long-term persistence in precipitation. Most climate models underestimate the spatial variability in temperature trends. The multimodel ensemble-average trend generally provides a conservative estimate of local/regional trends. The results of this study are generally not biased by the choice of observation datasets used, including Climatic Research Unit Time Series 3.1; temperature data from Hadley Centre/Climatic Research Unit, version 4; and precipitation data from Global Historical Climatology Network, version 2. © 2013 American Meteorological Society. 资助项目: NSF, National Science Foundation
; NSF, National Science Foundation
; NSF, National Science Foundation
; NSF, National Science Foundation
; NOAA, National Oceanic and Atmospheric Administration
; NASA, National Aeronautics and Space Administration
Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/51843
Appears in Collections: 气候变化事实与影响
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作者单位: Center for Ocean-Land-Atmosphere Studies, Calverton, MD, United States; School of Civil Engineering, Purdue University, West Lafayette, IN, United States; Department of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, VA, United States; Department of Agronomy, Department of Earth, Atmospheric and Planetary Sciences, Purdue University, West Lafayette, IN, United States
Recommended Citation:
Kumar S.,Merwade V.,Kinter III J.L.,et al. Evaluation of temperature and precipitation trends and long-term persistence in CMIP5 twentieth-century climate simulations[J]. Journal of Climate,2013-01-01,26(12)