A regression modeling approach for studying carbonate system variability in the northern Gulf of Alaska

摘要: [1] The northern Gulf of Alaska (GOA) shelf experiences carbonate system variability on seasonal and annual time scales, but little information exists to resolve higher frequency in this region. To using platforms-of-opportunity, we present multiple linear regression (MLR) models constructed from hydrographic data collected along the Northeast Pacific Global Ocean Ecosystems Dynamics (GLOBEC) Seward Line. The empirical algorithms predict dissolved inorganic carbon (DIC) total alkalinity (TA) observations nitrate (NO3−), temperature, salinity pressure surface 500 m, with R2s > 0.97 RMSE values 11 µmol kg−1 for DIC 9 µmol kg−1 TA. We applied these relationships high-resolution NO3− sets during a novel 20 h glider flight GLOBEC mesoscale SeaSoar survey. Results demonstrated time/space along-isopycnal aragonite saturations (Ωarag) associated dicothermal layer (a cold near-surface found high latitude oceans) that rivaled changes seen vertically through thermocline. survey captured uplift <100 m dense, high-pCO2 waters at break had been forced by passage Yakutat eddy. During event, saturation horizon (depth where Ωarag = 1) shoaled previously unseen depth GOA. This work is similar recent studies aimed predicting continental margin settings, albeit demonstrates NO3−-based approach can be high-latitude platforms capable high-frequency measurements.