Bering Sea Seasonal Predictability: Sea Ice and Bottom Temperature Model Output

Model simulation output from the Bering10K ROMS implementation supports a study on seasonal predictability. The dataset includes monthly mean temperature and ice coverage from downscaled Climate Forecast System and Canadian Coupled Climate Model retrospective forecasts. Author Kelly Kearney from the University of Washington produced this data for a submitted journal article.

Use Cases

• Evaluating seasonal forecast skill for sea ice based on anomaly correlation coefficients mentioned in the description
• Analyzing bottom temperature predictability across the eastern Bering Sea shelf using model hindcast simulations
• Comparing performance of different climate models (CFS vs. CanCM4) for regional downscaling applications

Strengths

• Data originates from a tailored regional ocean model (Bering10K ROMS) for the Bering Sea
• Includes output from two distinct downscaled climate model systems (CFS and CanCM4)
• Provides forecast skill metrics like anomaly correlation coefficient for validation

Limitations

• Column-level documentation is absent; field semantics must be inferred after download
• Row count is unknown, which may limit suitability assessment
• Last update date is unknown; freshness unverified

Provenance

Source

University of Washington

Collection Method

Output from the Bering10K ROMS model, an implementation of the Regional Ocean Modeling System.

Geography

Eastern Bering Sea shelf