TY  - JOUR
A1  - Mu, Longjiang
A1  - Nerger, Lars
A1  - Streffing, Jan
A1  - Tang, Qi
A1  - Niraula, Bimochan
A1  - Zampieri, Lorenzo
A1  - Loza, Svetlana N.
A1  - Goessling, Helge F.
T1  - Sea‐Ice Forecasts With an Upgraded AWI Coupled Prediction System
Y1  - 2022-12-22
VL  - 14
IS  - 12
JF  - Journal of Advances in Modeling Earth Systems
DO  - 10.1029/2022MS003176
PB  - 
N2  - A new version of the AWI Coupled Prediction System is developed based on the Alfred Wegener Institute Climate Model v3.0. Both the ocean and the atmosphere models are upgraded or replaced, reducing the computation time by a factor of 5 at a given resolution. This allowed us to increase the ensemble size from 12 to 30, maintaining a similar resolution in both model components. The online coupled data assimilation scheme now additionally utilizes sea‐surface salinity and sea‐level anomaly as well as temperature and salinity profile observations. Results from the data assimilation demonstrate that the sea‐ice and ocean states are reasonably constrained. In particular, the temperature and salinity profile assimilation has mitigated systematic errors in the deeper ocean, although issues remain over polar regions where strong atmosphere‐ocean‐ice interaction occurs. One‐year‐long sea‐ice forecasts initialized on 1 January, 1 April, 1 July and 1 October from 2003 to 2019 are described. To correct systematic forecast errors, sea‐ice concentration from 2011 to 2019 is calibrated by trend‐adjusted quantile mapping using the preceding forecasts from 2003 to 2010. The sea‐ice edge raw forecast skill is within the range of operational global subseasonal‐to‐seasonal forecast systems, outperforming a climatological benchmark for about 2 weeks in the Arctic and about 3 weeks in the Antarctic. The calibration is much more effective in the Arctic: Calibrated sea‐ice edge forecasts outperform climatology for about 45 days in the Arctic but only 27 days in the Antarctic. Both the raw and the calibrated forecast skill exhibit strong seasonal variations.
N2  - Plain Language Summary: Ocean data sparseness and systematic model errors pose problems for the initialization of coupled seasonal forecasts, especially in polar regions. Our global forecast system follows a seamless approach with refined ocean resolution in the Arctic. The new version presented here features higher computational efficiency and utilizes more ocean and sea‐ice observations. Ice‐edge forecasts outperform a climatological benchmark for about 1 month, comparable to established systems.
N2  - Key Points: We describe an upgrade of the AWI Coupled Prediction System with new ocean and atmosphere models and more observations assimilated. Independent evaluations show advances in the new version on the analysis of the sea‐ice and ocean states against the old one. Calibrated sea‐ice edge forecasts outperform a climatological benchmark for around 1 month in both hemispheres.
UR  - http://resolver.sub.uni-goettingen.de/purl?gldocs-11858/11386
ER  -