An updated regional model skill assessment for seasonal and interannual variability of bottom temperature across the eastern Bering Sea shelf
The Bering10K Regional Ocean Modeling System (ROMS) model is a high-resolution (10-km) regional ocean model that has been used over the past decade to investigate relationships between the physical environment and the eastern Bering Sea shelf ecosystem in both research and management contexts. Exten...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-02-01
|
| Series: | Frontiers in Marine Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/fmars.2025.1483945/full |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | The Bering10K Regional Ocean Modeling System (ROMS) model is a high-resolution (10-km) regional ocean model that has been used over the past decade to investigate relationships between the physical environment and the eastern Bering Sea shelf ecosystem in both research and management contexts. Extensive validation for this model has been conducted previously, particularly focused on bottom temperature, a key physical driver shaping ecosystem dynamics in this region. However, previous observations of bottom temperature were primarily limited to the summer months. Recent deployments of pop-up floats capable of overwinter measurements now allow us to extend the previous validation to other seasons. Here, we characterize bottom temperature on the southeastern Bering Sea shelf across time scales by combining data from our new pop-up floats with several existing temperature datasets. We then use this combination of data to systematically assess the skill of the Bering10K ROMS model in capturing these features, focusing on spatial variability in skill metrics and the potential processes leading to these patterns. We confirm that the model captures shelf-wide patterns in bottom temperature well, including mean patterns as well as both seasonal and interannual variability. However, a few areas of potential improvement were also identified: underestimated surface mixing in the model leads to delayed destratification across the middle and outer shelves, the position of the inner front may be offset slightly in the model, and bathymetric smoothing leads to poor representation near the shelf break and potentially underestimated flow onto the shelf through shelf break canyons. Overall, this paper presents the most detailed spatiotemporal analysis of this model’s skill in simulating bottom temperature across the eastern Bering Sea shelf to date and supplies a benchmark analysis framework that can be used for planned regional model transitions and improvements over the coming years. |
|---|---|
| ISSN: | 2296-7745 |