On the role of radiative forcing in inference of tropical convection using a neural operator climate emulator

We describe and evaluate the performance of a spherical Fourier harmonic neural operator climate emulator in training and autoregressive inference of the tropical atmosphere over the ERA5 reanalysis period 1985-2024. Inference and ablation studies performed with an ensemble of independent models at varying resolutions demonstrate stability and physical consistency with reliable emulation of key internal climate modes relevant to tropical variability. The models exhibit low biases over 40 year autoregressive in-sample inference for the modes considered. Examination of out-of-sample inference and ablation studies indicate that long term forecast skill of the key tropical climate processes and teleconnections is dependent on accurate prediction of large scale variations in the incident short wave radiation and to a lesser degree outward longwave radiation. Dependencies on resolution and the impact of inclusion of surface forcing as an additional boundary constraint are described.