The number of numerical model forecasts of ocean environmental conditions has greatly expanded in recent years, including biogeochemical variables. Forecasts can provide marine resource managers with advance warning of extreme events such as heatwaves and hypoxia, though forecast products are scarcer in high-latitude environments. The Bering Sea shelf is a large marine ecosystem that supports critical commercial, cultural, and subsistence ecosystem services that are vulnerable to extreme events and anthropogenic stressors such as ocean acidification (OA). Here, we use a regional oceanographic model of the Bering Sea to assess model forecast skill in predicting bottom water pH and aragonite saturation state (Ωarag) on lead times from 1 to 9 months. We simulate 28 years (1982–2010) of 3-member ensemble retrospective forecasts, initialized both in April and May following the retreat of winter sea ice and several months in advance of early fall when the most acidic bottom water conditions occur. The results suggest that the model is skillful (anomaly correlation coefficients > 0.5) in forecasting shelf-wide anomalies in bottom water pH and Ωarag, on lead times up to 9 months owing primarily to strong persistence. However, predictive skill for finer scale spatial anomalies is more limited and variable. Model forecast skill is also strong in Bristol Bay, home to the red king crab fishery that has faced recent closures and is threatened by OA. The model forecasts presented here can provide several months advanced notice for acidified water conditions and bolster a suite of products used to support evidence-based fisheries management.
Plain Language Summary
Similar to weather forecasts for the atmosphere, numerical models can also be used to forecast ocean conditions. The skill of these forecasts can be high up to several months in advance because the ocean has a relatively long memory and changes occur more slowly, particularly below the surface. The Bering Sea sustains substantial marine fisheries, which are threatened by changing ocean conditions such as increasing water acidity. Here we used an ocean model to test how well the model can forecast acidified bottom water conditions several months in advance. We did this by running a suite of reforecasts (i.e., we retroactively forecast years that have already occurred) and comparing to the model simulation of the conditions that did occur. Our results suggest that the model can generate skillful forecasts with lead times of up to 9 months, mainly because the conditions that occur at the start of our forecast tend to persist through the summer and into the fall. These forecasts can provide Bering Sea resource managers with advance warnings of water conditions that are harmful to marine species, such as Bristol Bay red king crab.
Pilcher D. J., Kearney K. A., Hermann A. J., Cheng W., Cross J. N. & Monacci N. M., 2026. Seasonal forecasts of pH and aragonite saturation for the Bering Sea shelf. Journal of Geophysical Research: Oceans 131: e2025JC023279. doi: 10.1029/2025JC023279. Article.
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