National Oceanic and
Atmospheric Administration
United States Department of Commerce


FY 2022

Dynamically downscaled projections of ocean acidification for the Bering Sea

Pilcher, D.J., J.N. Cross, A.J. Hermann, K.A. Kearney, W. Cheng, and J.T. Mathis

Deep-Sea Res. II, 198, 105055, doi: 10.1016/j.dsr2.2022.105055, View online (open access) (2022)

A regional ocean biogeochemical model for the Bering Sea is used to dynamically downscale three Earth System Models from the CMIP5 archive under the RCP 8.5 and RCP 4.5 scenarios. These continuous model runs, completed in conjunction with the Alaska Climate Integrated Modeling Project (ACLIM), span the 2006–2100 timeframe and project continued warming, freshening, and ocean acidification (OA) for the Bering Sea shelf region over the 21st Century, with larger magnitude changes in the RCP 8.5 scenario. The downscaled projections suggest that annual average surface seawater aragonite saturation state (Ωarag) for the Bering Sea shelf will decrease by 0.63–0.86 under RCP 8.5 and 0.18–0.43 under RCP 4.5 by 2100. Surface pH values decrease by 0.31–0.35 under RCP 8.5 and 0.07–0.13 under RCP 4.5. Seasonally, Ωarag < 1 conditions start to emerge for ∼2 months per year during winter between 2015-2030 under both climate change scenarios. Under RCP 8.5, the duration of these undersaturated conditions grows to ∼5 months per year by 2100, occurring from mid-October through mid-March. Under RCP 4.5, these conditions remain constrained to 2–3 months per year by 2100. In both scenarios, summer months maintain conditions of Ωarag > 1 due to primary productivity, though the maximum in Ωarag is greatly reduced under RCP 8.5. Spatially, the regions of greatest pH and Ωarag decline are the southeastern Bering Sea shelf and the outer shelf domain near the shelf break. Linear trends in carbonate variables between our downscaled simulations and the Earth System Model (ESM) output are comparable and indistinguishable compared to the model spread. However, bottom water trends differ somewhat between the ESM and our downscaled simulations, with the latter more consistently resolving the different shelf domains. The OA information provided by these downscaled simulations can help inform biological sensitivity experiments and longterm strategic planning for marine fisheries management.

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