Journal
JOURNAL OF CLIMATE
Volume 26, Issue 12, Pages 4168-4185Publisher
AMER METEOROLOGICAL SOC
DOI: 10.1175/JCLI-D-12-00259.1
Keywords
Climate change; Time series; Climate models; Trends; Regional effects
Categories
Funding
- National Science Foundation (NSF) Rapid Response [(RAPID) 1128164, NSF 0947837, NSF 0830068, NSF Career AGS 0847472, NOAA NA09OAR4310058, NASA NNX09AN50G]
- National Science Foundation
- Directorate For Geosciences
- Div Atmospheric & Geospace Sciences [0847472, GRANTS:13749175] Funding Source: National Science Foundation
- Directorate For Geosciences
- Div Atmospheric & Geospace Sciences [0947837] Funding Source: National Science Foundation
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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 degrees S-60 degrees 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 degrees C decade(-1)) captures the corresponding observed trend well (0.08 degrees 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.
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