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Diagnosing sea ice from the north american multi model ensemble and implications on mid-latitude winter climate

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Abstract

Arctic sea ice plays an important role in the climate system, moderating the exchange of energy and moisture between the ocean and the atmosphere. An emerging area of research investigates how changes, particularly declines, in sea ice extent (SIE) impact climate in regions local to and remote from the Arctic. Therefore, both observations and model estimates of sea ice become important. This study investigates the skill of sea ice predictions from models participating in the North American Multi-Model Ensemble (NMME) project. Three of the models in this project provide sea-ice predictions. The ensemble average of these models is used to determine seasonal climate impacts on surface air temperature (SAT) and sea level pressure (SLP) in remote regions such as the mid-latitudes. It is found that declines in fall SIE are associated with cold temperatures in the mid-latitudes and pressure patterns across the Arctic and mid-latitudes similar to the negative phase of the Arctic Oscillation (AO). These findings are consistent with other studies that have investigated the relationship between declines in SIE and mid-latitude weather and climate. In an attempt to include additional NMME models for sea-ice predictions, a proxy for SIE is used to estimate ice extent in the remaining models, using sea surface temperature (SST). It is found that SST is a reasonable proxy for SIE estimation when compared to model SIE forecasts and observations. The proxy sea-ice estimates also show similar relationships to mid-latitude temperature and pressure as the actual sea-ice predictions.

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Acknowledgements

We acknowledge the agencies that support the NMME system, and we thank the climate modeling groups (Environment Canada, NASA, NCAR, NOAA/GFDL, NOAA/NCEP, and University of Miami) for producing and making available their model output. NOAA/NCEP, NOAA/CTB, and NOAA/CPO jointly provided coordinating support and led development of the NMME system. Support was provided by the National Science Foundation (AGS-1338427), National Aeronautics and Space Administration (NNX14AM19G), the National Oceanic and Atmospheric Administration (NA14OAR4310160). The views expressed herein are those of the authors and do not necessarily reflect the views of these agencies. We also thank Kristin Harnos for her guidance processing NOAA/GFDL sea ice outputs on its native grid. Comments from Dr. S. Wang and two anonymous reviewers helped to improve a previous version of this manuscript.

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Authors and Affiliations

  1. Department of Atmospheric, Oceanic, and Earth Sciences, George Mason University, 4400 University Drive, Fairfax, VA, 22030, USA

    Akiko Elders

  2. Department of Atmospheric, Oceanic, and Earth Sciences and Center for Ocean-Land-Atmosphere Studies, George Mason University, 4400 University Drive, Fairfax, VA, 22030, USA

    Kathy Pegion

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  1. Akiko Elders
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  2. Kathy Pegion
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Correspondence to Akiko Elders.

Additional information

This paper is a contribution to the special collection on the North American Multi-Model Ensemble (NMME) seasonal prediction experiment. The special collection focuses on documenting the use of the NMME system database for research ranging from predictability studies, to multi-model prediction evaluation and diagnostics, to emerging applications of climate predictability for subseasonal to seasonal predictions. This special issue is coordinated by Annarita Mariotti (NOAA), Heather Archambault (NOAA), Jin Huang (NOAA), Ben Kirtman (University of Miami) and Gabriele Villarini (University of Iowa).

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Elders, A., Pegion, K. Diagnosing sea ice from the north american multi model ensemble and implications on mid-latitude winter climate. Clim Dyn 53, 7237–7250 (2019). https://doi.org/10.1007/s00382-017-4049-3

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  • DOI: https://doi.org/10.1007/s00382-017-4049-3

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