Estimating the Intrinsic Limit of Predictability Using a Stochastic Convection Scheme

Abstract

Global model simulations together with a stochastic convection scheme are used to assess the intrinsic limit of predictability that originates from convection up to planetary scales. The stochastic convection scheme has been shown to introduce an appropriate amount of variability onto the model grid without the need to resolve the convection explicitly. This largely reduces computational costs and enables a set of 12 cases equally distributed over 1 year with five ensemble members for each case, generated by the stochastic convection scheme. As a metric, difference kinetic energy at 300 hPa over the midlatitudes, both north and south, is used. With this metric the intrinsic limit is estimated to be about 17 days when a threshold of 80% of the saturation level is applied. The error level at 3.5 days roughly compares to the initial-condition uncertainty of the current ECMWF data assimilation system, which suggests a potential improvement of 3.5 forecast days through perfecting the initial conditions. Error-growth experiments that use a deterministic convection scheme show smaller errors of about half the size at early forecast times and an estimate of intrinsic predictability that is about 10% longer, confirming the overconfidence of deterministic convection schemes.