The California Current System: A multiscale overview and the development of a feature-oriented regional modeling system (FORMS)

17 USC 105 interim-entered record; under review.Over the past decade, the feature-oriented regional modeling methodology has been developed and applied in several ocean domains, including the western North Atlantic and tropical North Atlantic. This methodology is model-independent and can be utilized with or without satellite and/or in situ observations. Here we develop new feature-oriented models for the eastern North Pacific from 36◦ to 48◦N – essentially, most of the regional eastern boundary current. This is the firsttime feature-modeling has been applied to a complex eastern boundary current system. As a prerequisite to feature modeling, prevalent features that comprise the multiscale and complex circulation in the California Current system (CCS) are first overviewed. This description is based on contemporary understanding ofthe features and their dominant space and time scales of variability. A synergistic configuration of circulation features interacting with one another on multiple and sometimes overlapping space and time scales as a meander-eddy-upwelling system is presented. The second step is to define the feature-oriented regional modeling system (FORMS). The major multiscale circulation features include the mean flow and southeastward meandering jet(s) of the California Current (CC), the poleward flowing California Undercurrent (CUC), and six upwelling regions along the coastline. Next, the typical synoptic width, location, vertical extent, and core characteristics of these features and their dominant scales of variability are identified from past observational, theoretical and modeling studies. The parameterized features are then melded with the climatology, in situ and remotely sensed data, as available. The methodology is exemplified here for initialization of primitiveequation models. Dynamical simulations are run as nowcasts and short-term (4–6 weeks) forecasts using these feature models (FM) as initial fields and the Princeton Ocean Model (POM) for dynamics. The set of simulations over a 40-day period illustrate the applicability of FORMS to a transient eastern boundary current region such as the CCS. Comparisons are made with simulations initialized from climatology only. The FORMS approach increases skill in severalfactors, including the: (i) maintenance of the low-salinity pool in the core of the CC; (ii) representation of eddy activity inshore of the coastal transition zone; (iii) realistic eddy kinetic energy evolution; (iv) subsurface (intermediate depth) mesoscale feature evolution; and (v) deep poleward flow evolution.This work was funded by the Office of Naval Research grants N00014-03-1-0411 and N00014-03-1-0206 at the University of Massachusetts at Dartmouth. Leslie Rosenfeld’s participation was supported by ONR grant N00014-03-WR-20009. PFJL, PJH and WGL are grateful to ONR for support under grant N00014-08-1-1097, N00014-08-1-0680 and MURI-ASAP to the Massachusetts Institute of Technology

Adaptive Sampling Using Fleets of Underwater Gliders in the Presence of Fixed Buoys using a Constrained Clustering Algorithm

This paper presents a novel way to approach the problem of how to adaptively sample the ocean using fleets of underwater gliders. The technique is particularly suited for those situations where the covariance of the field to sample is unknown or unreliable but some information on the variance is known. The proposed algorithm, which is a variant of the well-known fuzzy C-means clustering algorithm, is able to exploit the presence of non-maneuverable assets, such as fixed buoys. We modified the fuzzy C-means optimization problem statement by including additional constraints. Then we provided an algorithmic solution to the new, constrained problem

Oceanographic and atmospheric conditions on the continental shelf north of the Monterey Bay during August 2006

A comprehensive data set from the ocean and atmosphere was obtained just north of the Monterey Bay as part of the Monterey Bay 2006 (MB06) field experiment. The wind stress, heat fluxes, and sea surface temperature were sampled by the Naval Postgraduate School’s TWIN OTTER research aircraft. In situ data were collected using ships, moorings, gliders and AUVs. Four data-assimilating numerical models were additionally run, including the Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®) model for the atmosphere and the Harvard Ocean Prediction System (HOPS), the Regional Ocean Modeling System (ROMS), and the Navy Coastal Ocean Model (NCOM) for the ocean. The scientific focus of the Adaptive Sampling and Prediction Experiment (ASAP) was on the upwelling/relaxation cycle and the resulting three-dimensional coastal circulation near a coastal promontory, in this case Point Año Nuevo, CA. The emphasis of this study is on the circulation over the continental shelf as estimated from the wind forcing, two ADCP moorings, and model outputs. The wind stress during August 2006 consisted of 3–10 day upwelling favorable events separated by brief 1–3 day relaxations. During the first two weeks there was some correlation between local winds and currents and the three models’ capability to reproduce the events. During the last two weeks, largely equator-ward surface wind stress forced the sea surface and barotropic poleward flow occurred over the shelf, reducing model skill at predicting the circulation. The poleward flow was apparently remotely forced by mesoscale eddies and alongshore pressure gradients, which were not well simulated by the models. The small, high-resolution model domains were highly reliant on correct open boundary conditions to drive these larger-scale poleward flows. Multiply-nested models were no more effective than well-initialized local models in this respect

Quantifying uncertainties in ocean preditions / Advances in Computational Oceanography

A multitude of physical and biological processes occur in the ocean over a wide range of temporal and spatial scales. Many of these processes are nonlinear and highly variable, and involve interactions across several scales and oceanic disciplines. For example, sound propagation is infl uenced by physical and biological properties of the water column and by the seabed. From observations and conservation laws, ocean scientists formulate models that aim to explain and predict dynamics of the sea. This formulation is intricate because it is challenging to observe the ocean on a sustained basis and to transform basic laws into generic but usable models. There are imperfections in both data and model estimates. It is important to quantify such uncertainties to understand limitations and identify the research needed to increase accuracies, which will lead to fundamental progress