Understanding sources of Northern Hemisphere uncertainty and forecast error in a medium‐range coupled ensemble sea‐ice prediction system

• Published in: Quarterly Journal of the Royal Meteorological Society
• Main Authors: Peterson, K. Andrew, Smith, Gregory C., Lemieux, Jean‐François, Roy, François, Buehner, Mark, Caya, Alain, Houtekamer, Pieter L., Lin, Hai, Muncaster, Ryan, Deng, Xingxiu, Dupont, Frédéric, Gagnon, Normand, Hata, Yukie, Martinez, Yosvany, Fontecilla, Juan Sebastian, Surcel‐Colan, Dorina
• Format: Article in Journal/Newspaper
• Language: English
• Published: Wiley 2022
• Subjects: Arctic; Canada; Climate change; Sea ice
• Online Access: http://dx.doi.org/10.1002/qj.4340; https://onlinelibrary.wiley.com/doi/pdf/10.1002/qj.4340; https://onlinelibrary.wiley.com/doi/full-xml/10.1002/qj.4340; https://rmets.onlinelibrary.wiley.com/doi/pdf/10.1002/qj.4340

Abstract The Global Ensemble Prediction System (GEPS) of Environment and Climate Change Canada was recently upgraded to a coupled atmosphere, ocean, and sea‐ice version from an uncoupled atmosphere‐only system. This has been operational since July 2019, with over a year of forecasts now available to evaluate the system throughout all seasons. Using metrics that score the forecast error in ice‐edge position, the spatial probability score and the integrated ice‐edge error, we investigate the spread–error relationship in probabilistic Arctic sea‐ice forecasts from the system and compare this with the skill of the system relative to persistence and a companion Global Deterministic Prediction System (GDPS). Within this ensemble framework, we explore the advantages of having a probabilistic forecast and probe its usefulness in addressing the errors in the system. Both the ensemble GEPS and the deterministic GDPS systems show enhanced sea‐ice prediction over persistence in all months except May and June, when significant biases exist in the systems in shallow‐sea and shelf regions. We attribute a significant portion of these biases to problems modelling landfast ice, but other sources of bias, including significant uncertainties in initializing and verifying sea‐ice analysis, also contribute. The lowest errors in the systems are found during September and continue at reasonably low levels through much of the boreal winter. The minimum and maximum extent periods, along with the early freeze‐up period, are shown to be periods for which the ensemble system offers enhanced benefits over a single deterministic forecast. For these periods, the errors are low and strongly correlated spatially with the ensemble spread. Nevertheless, we find that the ensemble system would likely still benefit from further improvement of the spread/error relationship in the system, currently hampered due to ensemble perturbations that are produced solely in the atmospheric component.