Previous studies have shown that various climate indices based on surface temperature can be used in detection and attribution studies of climate change. Besides global mean surface temperature, these indices are the contrast between surface temperature over land and over oceans, the temperature contrast between the Northern and Southern Hemispheres, the meridional temperature gradient in the Northern Hemisphere and the magnitude of the annual cycle of temperatures over land. The indices vary independently from the global mean at decadal timescales, yet show common responses to anthropogenic climate change. Collectively they are more useful in detecting and attributing climate change than global mean surface temperature alone. We use CMIP5 model data and investigate to what extent observed trends in surface temperature can be attributed to natural and anthropogenic forcings. The multi-model ensemble mean trend for all indices, except for NS, are either at or exceed the 5%–95% confidence interval for no trend. These trends cannot be explained by natural forcings only and additional forcings are required to replicate observed trends. Historical simulations with greenhouse gas forcings only resulted generally in trends in the indices that were larger than those in simulations with all historical forcings and observed. The difference in the trends in the indices between the simulations with all historical forcings and with greenhouse gas forcing only are ascribed to the effect of aerosols.