Functional autoregressive processes on a spherical domain for global aircraft-based atmospheric measurements

Motivated by global analysis of aircraft-based measurements of air pollutants and climate variables, and specifically the COVID-19 pandemic’s possible impact on ozone concentrations, a functional autoregressive model is proposed to capture global spatio-temporal variability, incorporating solar radiation cycles. Efficient estimation techniques are developed and means of suitable visualization demonstrated, paving the way for similar analyses in the future.