Skillful Coupled Atmosphere‐Ocean Forecasts on Interannual to Decadal Timescales Using a Linear Inverse Model

Abstract

Decadal prediction lies between the two extremes of short and long-term forecasting and involves uncertainty tied to initial conditions (ICs), internal variability, and external forcings. Climate mitigation and adaptation strategies require accurate short-to-long-term climate change predictions, as changing temperatures, air quality, and precipitation directly impact agriculture, water security, and human health. However, uncertain, dynamically evolving climate states on these timescales hinder policy making (e.g., Füssel, 2007). While climate prediction on centennial timescales is mostly a boundary condition problem that depends on external forcing (e.g., climate-change projections; see Branstator & Teng, 2010), interannual to decadal prediction lies between short-term weather predictions and long-term climate change projections, and thus involves uncertainties tied to both initialization and boundary conditions (e.g.