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Publication Date
29 September 2023

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 challenge to conduct initialized hindcasts 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. Here we run a set of hindcasts 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. 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 this method compared to the conventional methodology with a large hindcast data set, though there is a model dependence to the drifts in the two initialization methods.

Meehl, Gerald A., Ben Paul Kirtman, Anne A. Glanville, Jadwiga Richter, Nan A Rosenbloom, and Stephen Yeager. 2023. “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”. Climate Dynamics. Springer Science and Business Media LLC. doi:10.1007/s00382-023-06970-w.
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