A cross-scale model for 3D baroclinic circulation in estuary–plume–shelf systems: II. Application to the Columbia River

• Published in: Continental shelf research Vol. 25; no. 7; pp. 935 - 972
• Main Authors: Baptista, António M., Zhang, Yinglong, Chawla, Arun, Zulauf, Mike, Seaton, Charles, Myers III, Edward P., Kindle, John, Wilkin, Michael, Burla, Michela, Turner, Paul J.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.05.2005
• Subjects: and estuarine circulation; Brackish; coastal; Eulerian–Lagrangian methods; Finite differences; Finite volumes; Marine; Mathematical modeling; Ocean; Semi-implicit methods; Semi-implicit methods; Ocean; Mathematical modeling; Finite volumes; Finite differences; Eulerian–Lagrangian methods
• DOI: 10.1016/j.csr.2004.12.003
• ISSN: 0278-4343

This article is the second of a two-part paper on ELCIRC, an Eulerian-Lagrangian finite difference/finite volume model designed to simulate 3D baroclinic circulation across river-to-ocean scales. In part one (Zhang et al., 2004), we described the formulation of ELCIRC and assessed its baseline numerical skill. Here, we describe the application of ELCIRC within CORIE, a coastal margin observatory for the Columbia River estuary and plume. We first introduce the CORIE modeling system and its multiple modes of simulation, external forcings, observational controls, and automated products. We then focus on the evaluation of highly resolved, year-long ELCIRC simulations, using two variables (water level and salinity) to illustrate simulation quality and sensitivity to modeling choices. We show that, process-wise, simulations capture well important aspects of the response of estuarine and plume circulation to ocean, river, and atmospheric forcings. Quantitatively, water levels are robustly represented, while salinity intrusion and plume dynamics remain challenging. Our analysis highlights the benefits of conducting model evaluations over large time windows (months to years), to avoid significant localized biases. The robustness and computational efficiency of ELCIRC has proved invaluable in identifying and reducing non-algorithmic sources of errors, including parameterization (e.g., turbulence closure and stresses at the air-water interface) and external forcings (e.g., ocean conditions and atmospheric forcings).