A regional hindcast model simulating ecosystem dynamics, inorganic carbon chemistry, and ocean acidification in the Gulf of Alaska

The coastal ecosystem of the Gulf of Alaska (GOA) is especially vulnerable to the effects of ocean acidification and climate change. Detection of these long-term trends requires a good understanding of the system’s natural state. The GOA is a highly dynamic system that exhibits large inorganic carbo...

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Bibliographic Details
Published in:Biogeosciences
Main Authors: C. Hauri, C. Schultz, K. Hedstrom, S. Danielson, B. Irving, S. C. Doney, R. Dussin, E. N. Curchitser, D. F. Hill, C. A. Stock
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2020
Subjects:
Online Access:https://doi.org/10.5194/bg-17-3837-2020
https://doaj.org/article/e82475a3b2a54c7bb2e9f6b786257379
Description
Summary:The coastal ecosystem of the Gulf of Alaska (GOA) is especially vulnerable to the effects of ocean acidification and climate change. Detection of these long-term trends requires a good understanding of the system’s natural state. The GOA is a highly dynamic system that exhibits large inorganic carbon variability on subseasonal to interannual timescales. This variability is poorly understood due to the lack of observations in this expansive and remote region. We developed a new model setup for the GOA that couples the three-dimensional Regional Oceanic Model System (ROMS) and the Carbon, Ocean Biogeochemistry and Lower Trophic (COBALT) ecosystem model. To improve our conceptual understanding of the system, we conducted a hindcast simulation from 1980 to 2013. The model was explicitly forced with temporally and spatially varying coastal freshwater discharges from a high-resolution terrestrial hydrological model, thereby affecting salinity, alkalinity, dissolved inorganic carbon, and nutrient concentrations. This represents a substantial improvement over previous GOA modeling attempts. Here, we evaluate the model on seasonal to interannual timescales using the best available inorganic carbon observations. The model was particularly successful in reproducing observed aragonite oversaturation and undersaturation of near-bottom water in May and September, respectively. The largest deficiency in the model is its inability to adequately simulate springtime surface inorganic carbon chemistry, as it overestimates surface dissolved inorganic carbon, which translates into an underestimation of the surface aragonite saturation state at this time. We also use the model to describe the seasonal cycle and drivers of inorganic carbon parameters along the Seward Line transect in under-sampled months. Model output suggests that the majority of the near-bottom water along the Seward Line is seasonally undersaturated with respect to aragonite between June and January, as a result of upwelling and remineralization. Such an extensive ...