Advancing a Model-Validated Statistical Method for Decomposing the Key Oceanic Drivers of Regional Climate: Focus on Northern and Tropical African Climate Variability
The study validates and advances a statistical method for isolating the impacts of individual oceanic forcings on regional climate, with a focus here on northern and tropical Africa.
The statistical method can be used to develop observational benchmarks for evaluating ocean-land-atmosphere interactions in state-of-the-art global climate models, leading to process-based model weighting to reduce uncertainty in regional climate projections.
This study advances the practicality and stability of the traditional multivariate statistical method, Generalized Equilibrium Feedback Assessment (full-GEFA), for decomposing the key oceanic drivers of regional atmospheric variability, especially when available data records are short. An advanced stepwise-GEFA methodology is introduced, in which unimportant forcings within the forcing matrix are eliminated through stepwise selection. Method validation of stepwise-GEFA is performed using the CESM, with a focused application to northern and tropical Africa (NTA). First, a statistical assessment of the atmospheric response to each primary oceanic forcing is carried out by applying stepwise-GEFA to a fully coupled control run. Then, a dynamical assessment of the atmospheric response to individual oceanic forcings is performed through ensemble experiments by imposing sea surface temperature anomalies over focal ocean basins. Finally, to quantify the reliability of stepwise-GEFA, the statistical assessment is evaluated against the dynamical assessment in terms of four metrics. In CESM, tropical modes, namely El Niño Southern Oscillation, tropical Indian Basin, tropical Indian Dipole, and tropical Atlantic Niño modes, are the dominant oceanic controls of NTA climate.