Sensitivity of the ECMWF seasonal forecast model to CO2 and anthropogenic aerosol forcings: Experimental design and impact on climate trends

Abstract

Detection and attribution studies typically rely on free running climate models with modified anthropogenic forcings, yet they fail to reproduce key observed decadal trends. Despite reduced biases, higher predictive skill, large ensembles, and improved trends through frequent reinitialization, seasonal forecast models have not been used for this purpose. We introduce a new set of counterfactual seasonal hindcasts using the ECMWF coupled seasonal forecasting system based on alternative forcing scenarios by modifying atmospheric forcing and ocean and sea ice initial conditions. An observation based estimate of the forced ocean temperature signal is derived to amplify or remove this signal from the ocean initial conditions. Retrospective forecasts include a control configuration together with enhanced and reduced forcing experiments in which either CO2 increases together with doubled anthropogenic ocean warming or CO2 is fixed and the anthropogenic ocean-warming signal is removed. Additional experiments isolate aerosol forcing. The counterfactual hindcasts substantially alter long term temperature trends while largely preserving seasonal prediction skill, interannual variability, and model drift. Enhanced forcing strengthens several observed climate trends underestimated by the control, including top of atmosphere radiative fluxes and aspects of tropical Pacific atmospheric circulation. However, the coupled atmosphere ocean system fails to sustain the strengthened tropical Pacific temperature gradient through Bjerknes feedbacks, suggesting a fundamental model limitation. Aerosol forcing has little impact, likely because indirect aerosol effects are omitted. These results establish counterfactual seasonal hindcasts as a powerful tool for dynamic attribution and diagnosing model deficiencies in responses to anthropogenic climate forcing.