Robust Anthropogenic Signal Identified in the Seasonal Cycle of Tropospheric Temperature
Scientists at Lawrence Livermore National Laboratory in collaboration with colleagues from several institutions analyzed hundreds of climate simulations with different manifestations of internal climate variability. An anthropogenic fingerprint of tropospheric seasonal cycle change is identifiable in almost every simulation.
These results indicate that internal climate variability is insufficiently large to affect positive identification of the anthropogenic fingerprint of tropospheric seasonal cycle change.
Previous research identified an anthropogenic fingerprint in the amplitude of the seasonal cycle of tropospheric temperature. Increases in the annual cycle of tropospheric temperature are largest across the mid-latitudes, particularly in the northern hemisphere – a signal that appears in both coupled atmosphere-ocean and aquaplanet simulations. This fingerprint is evident in satellite observations, but the degree to which multidecadal internal variability influenced fingerprint detection has been unclear. To address this, the research team analyzed large initial condition ensembles from five different climate models. Each model realization has a distinct manifestation of internal variability stemming from perturbed initial conditions. Considering all ensemble members helps to determine the degree to which internal variability influences the detectability and detection time of the anthropogenic seasonal cycle fingerprint. Despite large (factor of 3) differences in the amplitude of multidecadal internal variability, the anthropogenic fingerprint was statistically identified in 239 of 240 large ensemble realizations. The anthropogenic fingerprint of tropospheric annual cycle changes is found in three of four satellite datasets. These results indicate that anthropogenic influence on the seasonal cycle of atmospheric temperature is evident over the satellite era, despite the presence of multidecadal internal variability. This robust signal is attributable to the distinct geographical pattern of the anthropogenic signal compared to the “noise” from multidecadal internal variability. The results suggest that research investigating changes in the Earth’s seasonal cycles can help to identify and document human influence on climate.