Revisiting Aerosol Effects in Global Climate Models Using an Aerosol Lidar Simulator

Aerosol effects are considered a major source of uncertainty in global climate models and the direct and indirect radiative forcings have strong model dependency. These forcings are routinely evaluated (and calibrated) against observations, among them satellite retrievals are greatly used for their near-global coverage. However, the forcings calculated from model output are not directly comparable with those computed from satellite retrievals since sampling and algorithmic differences (such as cloud screening, noise reduction, and retrieval) between models and observations are not accounted for. It is our hypothesis that the conventional model validation procedures for comparing satellite observations and model simulations can mislead model development and introduce biases. Hence, we have developed an aerosol lidar simulator for global climate models that simulates the CALIOP lidar signal at 532nm. The simulator uses the same algorithms as those used to produce the "GCM-oriented CALIPSO Aerosol Product" to (1) objectively sample lidar signal profiles; and (2) derive aerosol fields (e.g., extinction profile, aerosol type, etc) from lidar signals. This allows us to sample and derive aerosol fields in the model and real atmosphere in identical ways. Using the Department of Energy's ACME model simulations, we found that the simulator-retrieved aerosol distribution and aerosol-cloud interactions are significantly different from those computed from conventional approaches, and that the model is much closer to satellite estimates than previously believed.