Climate change is known to cause deoxygenation in the open ocean, but its effects on eutrophic and seasonally hypoxic estuaries and coastal oceans are less clear. Using Chesapeake Bay as a study site, we conducted climate downscaling projections for dissolved oxygen and found that the hypoxic and anoxic volumes would increase by 10-30% between the late 20th and mid-21st century. A budget analysis of dissolved oxygen in the bottom water revealed differing physical and biogeochemical responses to climate change. Sea level rise and larger winter-spring runoff led to stronger stratification and large reductions in the vertical oxygen supply to the bottom water. On the other hand, warming led to earlier initiation of hypoxia, accompanied by weaker summer respiration and more rapid termination of hypoxia. Decreasing solubility due to warming accounted for about 50% of the reduction in the bottom-water oxygen content.

Secular tidal trends are present in many tide gauge records, but their causes are often unclear. This study examines trends in tides over the last century in the Chesapeake and Delaware Bays. Statistical models show negative M2 amplitude trends at the mouths of both bays, while some upstream locations have insignificant or positive trends. To determine whether sea level rise is responsible for these trends, we include a term for mean sea level in the statistical models and compare the results with predictions from numerical and analytical models. The observed and predicted sensitivities of M2 amplitude and phase to mean sea level are similar, although the numerical model amplitude is less sensitive to sea level. The sensitivity occurs as a result of strengthening and shifting of the amphidromic system in the Chesapeake Bay and decreasing frictional effects and increasing convergence in the Delaware Bay. After accounting for the effect of sea level, significant negative background M2 and S2 amplitude trends are present; these trends may be related to other factors such as dredging, tide gauge errors, or river discharge. Projected changes in tidal amplitudes due to sea level rise over the 21st century are substantial in some areas, but depend significantly on modeling assumptions.

Efforts to manage living marine resources (LMRs) under climate change need projections of future ocean conditions, yet most global climate models (GCMs) poorly represent critical coastal habitats. GCM utility for LMR applications will increase with higher spatial resolution but obstacles including computational and data storage costs, obstinate regional biases, and formulations prioritizing global robustness over regional skill will persist. Downscaling can help address GCM limitations, but significant improvements are needed to robustly support LMR science and management. We synthesize past ocean downscaling efforts to suggest a protocol to achieve this goal. The protocol emphasizes LMR-driven design to ensure delivery of decision-relevant information. It prioritizes ensembles of downscaled projections spanning the range of ocean futures with durations long enough to capture climate change signals. This demands judicious resolution refinement, with pragmatic consideration for LMR-essential ocean features superseding theoretical investigation. Statistical downscaling can complement dynamical approaches in building these ensembles. Inconsistent use of bias correction indicates a need for objective best practices. Application of the suggested protocol should yield regional ocean projections that, with effective dissemination and translation to decision-relevant analytics, can robustly support LMR science and management under climate change.