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

Abstract

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.

Evaluation of CMIP5 Global Climate Models over the Volta Basin: Precipitation

“…Although the models are unable to simulate the observed pattern, the observed variability is simulated relatively well by the CCSM4 and the EM over the basin and the three belts. In the case of the EM, this study is consistent with previous studies (e.g., [19,20]) that suggest better performances for EMs.…”

“…ey also indicated the superior performance of the multimodel ensemble mean to the individual models. Kumar et al [20] have also evaluated temperature and precipitation trends in 19 CMIP5 GCMs, focusing on continental areas (60°S-60°N) for the period. ey showed that there are large uncertainties in the models in simulating local-scale temperature and precipitation trends.…”

Modeling the effects of climate change on water, sediment, and nutrient yields from the Maumee River watershed

“…CMIP5 models were chosen based on research by Kumar et al (2013) that evaluated the performance of 19 CMIP5 models in replicating historical data trends. Of the 19 models tested, CCSM4.0 had the highest correlation with historical precipitation trends, while GFDL and MIROC had the highest correlation with historical temperature trends (Kumar et al, 2013).…”

The Towuti Drilling Project: paleoenvironments, biological evolution, and geomicrobiology of a tropical Pacific lake

“…Our ability to make accurate predictions about future climate, and in particular future precipitation, thus rests on our understanding of the tropical Pacific climate under different climate boundary conditions than today. Global climate models exhibit significant inter-model differences in their simulations of recent and future precipitation change over the IPWP (Kumar et al, 2013;Meehl et al, 2007), as do simulations of IPWP precipitation under glacial boundary conditions (DiNezio et al, 2011;DiNezio and Tierney, 2013), motivating scientific drilling at Lake Towuti.…”