A.M. Moore

Spatially resolved upwelling in the California Current System and its connections to climate variability

A historical analysis of California Current System (CCS) circulation, performed using the Regional Ocean Modeling System with four-dimensional variational data assimilation, was used to study upwelling variability during the 1988-2010 period. We examined upwelling directly from the vertical velocity field, which elucidates important temporal and spatial variability not captured by traditional coastal upwelling indices. Through much of the CCS, upwelling within 50 km of the coast has increased, as reported elsewhere. However, from 50 to 200 km offshore, upwelling trends are negative and interannual variability is 180 ◦ out of phase with the nearshore signal. This cross-shore pattern shows up as the primary mode of variability in central and northern CCS vertical velocity anomalies, accounting for ∼40% of the total variance. Corresponding time series of the dominant modes in the central and northern CCS are strongly correlated with large-scale climate indices, suggesting that climate fluctuations may alternately favor different biological communities.

Assessing the impact of observations on ocean forecasts and reanalyses: Part 2, Regional applications

The value of global (e.g. altimetry, satellite sea-surface temperature, Argo) and regional (e.g. radars, gliders, instrumented mammals, airborne profiles and biogeochemical) observation-types for monitoring the mesoscale ocean circulation and biogeochemistry is demonstrated using a suite of global and regional prediction systems and remotely-sensed data. A range of techniques is used to demonstrate the value of different observation-types to regional systems and the benefit of high-resolution and adaptive sampling for monitoring the mesoscale circulation. The techniques include Observing System Experiments, Observing System Simulation Experiments, adjoint sensitivities, representer matrix spectrum, observation footprints and spectral analysis. It is shown that local errors in global and basin-scale systems can be significantly reduced when assimilating observations from regional observing systems.

The Inverse Ocean Modeling System. Part II: Applications

The Inverse Ocean Modeling (IOM) System is a modular system for constructing and running weakconstraint four-dimensional variational data assimilation (W4DVAR) for any linear or nonlinear functionally smooth dynamical model and observing array. The IOM has been applied to four ocean models with widely varying characteristics. The Primitive Equations Z-coordinate-Harmonic Analysis of Tides (PEZHAT) and the Regional Ocean Modeling System (ROMS) are three-dimensional, primitive equations models while the Advanced Circulation model in 2D (ADCIRC-2D) and Spectral Element Ocean Model in 2D (SEOM-2D) are shallow-water models belonging to the general finite-element family. These models, in conjunction with the IOM, have been used to investigate a wide variety of scientific phenomena including tidal, mesoscale, and wind-driven circulation. In all cases, the assimilation of data using the IOM provides a better estimate of the ocean state than the model alone.

Coastal Ocean Forecasting: science foundation and user benefits

The advancement of Coastal Ocean Forecasting Systems (COFS) requires the support of continuous scientific progress addressing: (a) the primary mechanisms driving coastal circulation; (b) methods to achieve fully integrated coastal systems (observations and models), that are dynamically embedded in larger scale systems; and (c) methods to adequately represent air-sea and biophysical interactions. Issues of downscaling, data assimilation, atmosphere-wave-ocean couplings and ecosystem dynamics in the coastal ocean are discussed. These science topics are fundamental for successful COFS, which are connected to evolving downstream applications, dictated by the socioeconomic needs of rapidly increasing coastal populations.