For the first, trends in bias and drift introduce higher skill estimates earlier and later in the hindcast period due to the trends that contribute to skill. Three methods of computing anomalies, one as differences from a long term model climatology, another as bias-adjusted differences from the previous 15 year average from observations, and a third as differences from the previous 15 year average from the model, are contrasted and each is shown to have limitations. We examine several methods of calculating anomalies using the Decadal Prediction Large Ensemble (DPLE) using the Community Earth System Model (CESM) initialized hindcasts and focus on Pacific and Atlantic SSTs to illustrate issues with more » anomaly calculations. Differences in trends between initial states and drifted states, combined with bias and drift, introduce complexities in calculating anomalies to assess skill of initialized predictions. Bias and drift are among the greatest challenges facing initialized prediction today. In initialized seasonal to decadal (S2D) predictions, model hindcasts rapidly drift away from the initial observed state and converge toward a preferred state characterized by systematic error, or bias. (PNNL), Richland, WA (United States) University Corporation for Atmospheric Research (UCAR), Boulder, CO (United States) Sponsoring Org.: USDOE Office of Science (SC), Biological and Environmental Research (BER) OSTI Identifier: 1828865 Alternate Identifier(s): OSTI ID: 1923917 Report Number(s): PNNL-SA-166611 Journal ID: ISSN 1942-2466 Grant/Contract Number: AC05-76RL01830 89243018SSC000007 Resource Type: Journal Article: Accepted Manuscript Journal Name: Journal of Advances in Modeling Earth Systems Additional Journal Information: Journal Volume: 13 Journal Issue: 9 Journal ID: ISSN 1942-2466 Publisher: American Geophysical Union (AGU) Country of Publication: United States Language: English Subject: 54 ENVIRONMENTAL = , Publication Date: Research Org.: Pacific Northwest National Lab.
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