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    Evaluation of Temperature and Precipitation Trends and Long-Term Persistence in CMIP5 Twentieth-Century Climate Simulations

    Source: Journal of Climate:;2013:;volume( 026 ):;issue: 012::page 4168
    Author:
    Kumar, Sanjiv
    ,
    Merwade, Venkatesh
    ,
    Kinter, James L.
    ,
    Niyogi, Dev
    DOI: 10.1175/JCLI-D-12-00259.1
    Publisher: American Meteorological Society
    Abstract: he 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.
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      Evaluation of Temperature and Precipitation Trends and Long-Term Persistence in CMIP5 Twentieth-Century Climate Simulations

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    contributor authorKumar, Sanjiv
    contributor authorMerwade, Venkatesh
    contributor authorKinter, James L.
    contributor authorNiyogi, Dev
    date accessioned2017-06-09T17:06:35Z
    date available2017-06-09T17:06:35Z
    date copyright2013/06/01
    date issued2013
    identifier issn0894-8755
    identifier otherams-79507.pdf
    identifier urihttp://onlinelibrary.yabesh.ir/handle/yetl/4222295
    description abstracthe 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.
    publisherAmerican Meteorological Society
    titleEvaluation of Temperature and Precipitation Trends and Long-Term Persistence in CMIP5 Twentieth-Century Climate Simulations
    typeJournal Paper
    journal volume26
    journal issue12
    journal titleJournal of Climate
    identifier doi10.1175/JCLI-D-12-00259.1
    journal fristpage4168
    journal lastpage4185
    treeJournal of Climate:;2013:;volume( 026 ):;issue: 012
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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