Observing system simulation experiments of dissolved oxygen monitoring in Massachusetts Bay

Abstract

Observing system simulation experiments (OSSEs) were performed in Massachusetts Bay for the design of optimal monitoring sites for dissolved oxygen (DO) measurements. Experiments were carried out using the Ensemble Kalman Filter (EnKF) for data assimilation with focus on initial and boundary perturbations. Running a well-validated water quality model with a perturbed initial field of DO but “true” boundary forcing conditions, the model is capable of restoring DO back to the true state without data assimilation over a recovery time scale of about a month. Since DO in Massachusetts Bay has a bay-wide correlation scale, placing a monitoring site of DO near the northern boundary or at a location that has maximum correlation to the entire domain can shorten the restoring time to a week. Running the model with perturbed boundary forcing without data assimilation, the results show that the errors propagate into Massachusetts Bay following the inflow from the northern boundary and spread southward to Cape Cod Bay over a time scale of about a month. Using a DO monitoring site located near the northern entrance, the data assimilation can efficiently control the error propagation and prevent the model field from deviating from the true state. The model shows that the inflow from the northern entrance, which is connected to the upstream Western Maine Coastal Current, plays an important role in controlling the DO variation in Massachusetts Bay, and the residence time of the bay controlled by this flow is about one month. Understanding the upstream boundary-control nature of this system is critical for optimal design of sampling strategies of water quality variables in this region.