Testing An Optimal Fingerprinting Method to Separate the Greenhouse Gas and Aerosol Forced Responses in Observations

A central challenge in climate science is the assessment and quantification of anthropogenic temperature and precipitation change patterns in space and time, as well as the individual contributions from anthropogenic greenhouse gas (GHG) and aerosol (AER) forcings. While single model initial condition large ensembles allow robust separation of forced responses from internal variability and single-forcing simulations allow for the direct interrogation of individual drivers of climate change, understanding the interplay between AER and GHG responses remains difficult in observations, where only one realization of the climate system, subject to all forcings, is available.
 
Signal-to-Noise Maximizing Pattern Optimal Fingerprinting (SNMP-OF) offers a promising method to estimate the responses to AER and GHG forcing in a single climate realization. In a first step, Signal-to-Noise Maximizing Pattern (SNMP) analysis is used to characterize spatiotemporal anomaly patterns that are common across ensembles of single-forcing GHG or AER simulations and therefore likely represent an externally forced signal. Optimal Fingerprinting (OF) projects these patterns onto single ensemble members or observations to estimate the contribution of anthropogenic GHG and AER forcings to global temperature and precipitation changes. CNRM-CM6.1, CanESM5, HadGEM3, IPSL-CM6A, MIROC6 and CESM2 single- and all-forcings simulations of near-surface air temperature and total precipitation rate are used to test the method, by iteratively retrieving the forced response with SNMP from 5 of the 6 models and testing it with OF on single ensemble members of the remaining model. The skill in estimating the forced response in the left out model is compared to a benchmark method which is based on a simple scaling of the other 5 models. SNMP-OF is then used to estimate the AER and GHG forced responses in temperature and precipitation within observations. 
 
Since GHG and AER exert partly opposing effects on the climate system, their separate quantification is essential for a physically consistent understanding of anthropogenic climate change and may provide more causal insight into observed climate trends.