Seasonal Predictability of Sea Ice and Bottom Temperature Across the Eastern Bering Sea Shelf

Kearney, K. A.; Alexander, M.; Aydin, K.; Cheng, W.; Hermann, A. J.; Hervieux, G.; Ortiz, I.

doi:10.1029/2021JC017545

i

Seasonal Predictability of Sea Ice and Bottom Temperature Across the Eastern Bering Sea Shelf

Supporting Files

2021
By Kearney, K. A. ; Alexander, M. ; Aydin, K. ; ...

Details

Journal Title:

Journal of Geophysical Research: Oceans
Personal Author:

Kearney, K. A. ; Alexander, M. ; Aydin, K. ; Cheng, W. ; Hermann, A. J. ; Hervieux, G. ; Ortiz, I.
NOAA Program & Office:

CIRES (Cooperative Institute for Research in Environmental Sciences) ; JISAO (Joint Institute for the Study of the Atmosphere and Ocean) ; CICOES (Cooperative Institute for Climate, Ocean and Ecosystem Studies) ; OAR (Oceanic and Atmospheric Research) ; CPO (Climate Program Office) ; Integrated Ecosystem Assessment ; NMFS (National Marine Fisheries Service) ; AFSC (Alaska Fisheries Science Center)
Description:

Seasonal sea ice plays a key role in shaping the ecosystem dynamics of the eastern Bering Sea shelf. In particular, it leads to the formation of a characteristic pool of cold water that covers the bottom of the shelf from winter through summer; the extent of this cold pool is often used as a management index for distribution, productivity, recruitment, and survival of commercially important fish and shellfish species. Here, we quantify our ability to seasonally forecast interannual variability in Bering Sea bottom temperature and sea ice extent. Retrospective forecast simulations from two global forecast models are downscaled using a regional ocean model; the retrospective forecast simulations include 9-month to 12-month forecasts spanning 1982–2010. We find that dynamic forecasting can predict summer bottom temperatures across the eastern Bering Sea shelf with lead times of up to 4 months. The majority of the prediction skill derives from the persistence signal, and a persistence forecast is comparably skillful to the dynamic forecast at these lead times. However, forecast skill of sea ice advance and retreat is low when a forecast model is initialized before or during the ice season (October–February); this limits the ability of either dynamic or persistence models to predict summer bottom temperatures when initialized across the late fall to early spring months.
Keywords:

Integrated Ecosystem Assessment Seasonal Forecast Integrated Ecosystem Assessment Seasonal Forecast Modeling, Analysis, Predictions, and Projections (MAPP)
Source:

Journal of Geophysical Research: Oceans, 126, e2021JC017545
DOI:

https://doi.org/10.1029/2021JC017545
Document Type:

Journal Article
Funding:

Grant no. NA17OAR4310104 ; Grant no. NA15OAR4320063
Place as Subject:

Bering Sea
License:

https://creativecommons.org/licenses/by/4.0/
Rights Information:

CC BY
Compliance:

Submitted
Main Document Checksum:

urn:sha256:72d902465b49641ed83994dff8d07de91777d5b7fb36e7ad2c57231f88efce2b
Download URL:

https://repository.library.noaa.gov/view/noaa/44760/noaa_44760_DS1.pdf
File Type:

[PDF - 7.88 MB ]

Available dataset

html

ON THIS PAGE

Details Supporting Files

The NOAA IR serves as an archival repository of NOAA-published products including scientific findings, journal articles, guidelines, recommendations, or other information authored or co-authored by NOAA or funded partners. As a repository, the NOAA IR retains documents in their original published format to ensure public access to scientific information.