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

被引:174
作者
Kumar, Sanjiv [1 ]
Merwade, Venkatesh [2 ]
Kinter, James L., III [1 ,3 ]
Niyogi, Dev [4 ,5 ]
机构
[1] Ctr Ocean Land Atmosphere Studies, Calverton, MD 20705 USA
[2] Purdue Univ, Sch Civil Engn, W Lafayette, IN 47907 USA
[3] George Mason Univ, Dept Atmospher Ocean & Earth Sci, Fairfax, VA 22030 USA
[4] Purdue Univ, Dept Agron, W Lafayette, IN 47907 USA
[5] Purdue Univ, Dept Earth Atmospher & Planetary Sci, W Lafayette, IN 47907 USA
基金
美国国家科学基金会;
关键词
Climate change; Time series; Climate models; Trends; Regional effects; AIR-TEMPERATURE; WARMING HOLE; TESTS;
D O I
10.1175/JCLI-D-12-00259.1
中图分类号
P4 [大气科学(气象学)];
学科分类号
0706 ; 070601 ;
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 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.
引用
收藏
页码:4168 / 4185
页数:18
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