Abstract

Anthropogenic aerosols and greenhouse gases are the dominant drivers of forced climate change over the past century, with contrasting effects on earth’s radiative energy balance. In addition to their opposing effects on global-mean temperature, they impact regional climate in distinctive ways due to their differing geographical distributions and temporal variations. Here, we examine their unique fingerprints on the evolution of the coupled ocean-atmosphere-land-ice system using a suite of climate model experiments designed to isolate their influences from other sources of forced climate change. The large number of realizations in our experiments also allows us to assess how detectable their impacts are relative to internal fluctuations of the climate system.

Further Details

The evolving roles of anthropogenic aerosols (AER) and greenhouse gases (GHG) in driving large-scale patterns of precipitation, temperature and atmospheric circulation trends during 1920–2080 are studied using a new set of ‘‘all-but-one-forcing’’ initial-condition Large Ensembles (LEs) with the Community Earth System Model version 1 (CESM1), which complement the original ‘‘all-forcing’’ CESM1 LE (ALL). The large number of ensemble members (15–20) in each of the new LEs enables regional impacts of AER and GHG to be isolated from the noise of the model’s internal variability. Our analysis approach, based on running 50-yr trends, accommodates geographical and temporal changes in patterns of forcing and response. AER are shown to be the primary driver of large-scale patterns of externally forced trends in ALL before the late 1970s, and GHG to dominate thereafter. The AER and GHG forced trends are spatially distinct except during the 1970s transition phase when aerosol changes are mainly confined to lower latitudes. The transition phase is also characterized by a relative minimum in the amplitude of forced trend patterns in ALL, due to a combination of reduced AER and partially offsetting effects of AER and GHG. Internal variability greatly limits the detectability of AER- and GHG-forced trend patterns in individual realizations based on pattern correlation metrics, especially during the historical period, highlighting the need for LEs. The detectability of the AER and GHG forced trend patterns is also low in the observations, although model biases in patterns of forced response and signal-to-noise may affect this estimate.