Evaluating Skill in Predicting the Interdecadal Pacific Oscillation in Initialized Decadal Climate Prediction Hindcasts in E3SMv1 and CESM1 Using Two Different Initialization Methods and a Small Set of Start Years
It is a daunting computational challenge to conduct initialized multi-year Earth system predictions with enough ensemble members and associated start years to form a drifted climatology from which to compute the anomalies necessary to quantify the skill of the hindcasts when compared to observations. This limits the ability to experiment with case studies and other applications where only a few initial years are needed. We explore new ways to approach this problem.
Through the analysis of the standard 1-degree resolution E3SMv1 and CESM1 initialized multi-year Earth system predictions, we show that there is comparable skill for predicting spatial patterns of multi-year Pacific sea surface temperature anomalies in the domain of the Interdecadal Pacific Oscillation using two different initialization methods and the historical large ensembles from the models to represent a drifted model climatology, as opposed to having to run a large and expensive hindcast set of simulations for every new experiment or model formulation. This result opens up new directions in the field of multi-year Earth system prediction to allow case studies and limited start years to study processes, something that was previously not thought to be feasible.
A set of multi-year Earth system predictions are run with CESM1 and E3SMv1 using two different initialization methods for a limited set of start years, and use the respective uninitialized free-running historical simulations to form the model climatologies. Since the drifts from the observed initial states in the hindcasts toward the uninitialized model state are large and rapid, after a few years the drifted initialized models approach the uninitialized model climatological errors. Therefore, hindcasts from the limited start years can use the uninitialized climatology to represent the drifted model states after about lead year 3, providing a means to compute forecast anomalies in the absence of a large hindcast sample.