The value of sustained ocean observations for sea-ice predictions in the Barents Sea

Bushuk, Mitchell; Yang, Xiaosong; Winton, Michael; Msadek, Rym; Harrison, Matthew; Rosati, Anthony; Gudgel, Rich

doi:10.1175/JCLI-D-19-0179.1

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The value of sustained ocean observations for sea-ice predictions in the Barents Sea

2019
By Bushuk, Mitchell ; Yang, Xiaosong ; Winton, Michael ; ...
Source: Journal of Climate, 32(20), 7017-7035, 2019

[PDF-3.07 MB]

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Journal Title:

Journal of Climate
Personal Author:

Bushuk, Mitchell ; Yang, Xiaosong ; Winton, Michael ; Msadek, Rym ; Harrison, Matthew ; ... More +

Bushuk, Mitchell ; Yang, Xiaosong ; Winton, Michael ; Msadek, Rym ; Harrison, Matthew ; Rosati, Anthony ; Gudgel, Rich Less -
NOAA Program & Office:

OAR (Oceanic and Atmospheric Research) ; GFDL (Geophysical Fluid Dynamics Laboratory) ; CPO (Climate Program Office)

OAR (Oceanic and Atmospheric Research) ; GFDL (Geophysical Fluid Dynamics Laboratory) ; CPO (Climate Program Office) Less -
Description:

Dynamical prediction systems have shown potential to meet the emerging need for seasonal forecasts of regional Arctic sea ice. Observationally constrained initial conditions are a key source of skill for these predictions, but the direct influence of different observation types on prediction skill has not yet been systematically investigated. In this work, we perform a hierarchy of observing system experiments with a coupled global data assimilation and prediction system to assess the value of different classes of oceanic and atmospheric observations for seasonal sea ice predictions in the Barents Sea. We find notable skill improvements due to the inclusion of both sea surface temperature (SST) satellite observations and subsurface conductivity–temperature–depth (CTD) measurements. The SST data are found to provide the crucial source of interannual variability, whereas the CTD data primarily provide climatological and trend improvements. Analysis of the Barents Sea ocean heat budget suggests that ocean heat content anomalies in this region are driven by surface heat fluxes on seasonal time scales.
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Numerical Weather Forecasting Sea Ice
Source:

Journal of Climate, 32(20), 7017-7035, 2019
DOI:

https://doi.org/10.1175/JCLI-D-19-0179.1
Document Type:

Journal Article
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Barents Sea
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urn:sha256:fed65bde25b7628d788e4856c5591f8575c0280d5ce32f2d9928acd9d0b137ed
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The value of sustained ocean observations for sea-ice predictions in the Barents Sea

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