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Kim, SY, Cornuelle BD.  2015.  Coastal ocean climatology of temperature and salinity off the Southern California Bight: Seasonal variability, climate index correlation, and linear trend. Progress in Oceanography. 138:136-157.   10.1016/j.pocean.2015.08.001   AbstractWebsite

A coastal ocean climatology of temperature and salinity in the Southern California Bight is estimated from conductivity-temperature-depth (CTD) and bottle sample profiles collected by historical California Cooperative Oceanic Fisheries Investigation (CalCOFI) cruises (1950-2009; quarterly after 1984) off southern California and quarterly/monthly nearshore CTD surveys (within 30 km from the coast except for the surfzone; 1999-2009) off San Diego and Los Angeles. As these fields are sampled regularly in space, but not in time, conventional Fourier analysis may not be possible. The time dependent temperature and salinity fields are modeled as linear combinations of an annual cycle and its five harmonics, as well as three standard climate indices (El Nino-Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), North Pacific Gyre Oscillation (NPGO)), the Scripps Pier temperature time series, and a mean and linear trend without time lags. Since several of the predictor indices are correlated, the indices are successively orthogonalized to eliminate ambiguity in the identification of the contributed variance of each component. Regression coefficients are displayed in both vertical transects and horizontal maps to evaluate (1) whether the temporal and spatial scales of the two data sets of nearshore and offshore observations are consistent and (2) how oceanic variability at a regional scale is related to variability in the nearshore waters. The data-derived climatology can be used to identify anomalous events and atypical behaviors in regional-scale oceanic variability and to provide background ocean estimates for mapping or modeling. (C) 2015 Elsevier Ltd. All rights reserved.

Mazloff, MR, Gille ST, Cornuelle B.  2014.  Improving the geoid: Combining altimetry and mean dynamic topography in the California coastal ocean. Geophysical Research Letters. 41:8944-8952.   10.1002/2014gl062402   AbstractWebsite

Satellite gravity mapping missions, altimeters, and other platforms have allowed the Earth's geoid to be mapped over the ocean to a horizontal resolution of approximately 100km with an uncertainty of less than 10cm. At finer resolution this uncertainty increases to greater than 10cm. Achieving greater accuracy requires accurate estimates of the dynamic ocean topography (DOT). In this study two DOT estimates for the California Current System with uncertainties less than 10cm are used to solve for a geoid correction field. The derived field increases the consistency between the DOTs and along-track altimetric observations, suggesting it is a useful correction to the gravitational field. The correction is large compared to the dynamic ocean topography, with a magnitude of 15cm and significant structure, especially near the coast. The results are evidence that modern high-resolution dynamic ocean topography products can be used to improve estimates of the geoid.

Di Lorenzo, E, Moore AM, Arango HG, Cornuelle BD, Miller AJ, Powell B, Chua BS, Bennett AF.  2007.  Weak and strong constraint data assimilation in the inverse Regional Ocean Modeling System (ROMS): Development and application for a baroclinic coastal upwelling system. Ocean Modelling. 16:160-187.   10.1016/j.ocemod.2006.08.002   AbstractWebsite

We describe the development and preliminary application of the inverse Regional Ocean Modeling System (ROMS), a four dimensional variational (4DVAR) data assimilation system for high-resolution basin-wide and coastal oceanic flows. Inverse ROMS makes use of the recently developed perturbation tangent linear (TL), representer tangent linear (RP) and adjoint (AD) models to implement an indirect representer-based generalized inverse modeling system. This modeling framework is modular. The TL, RP and AD models are used as stand-alone sub-models within the Inverse Ocean Modeling (IOM) system described in [Chua, B.S., Bennett, A.F., 2001. An inverse ocean modeling system. Ocean Modell. 35 137-165.]. The system allows the assimilation of a wide range of observation types and uses an iterative algorithm to solve nonlinear assimilation problems. The assimilation is performed either under the perfect model assumption (strong constraint) or by also allowing for errors in the model dynamics (weak constraints). For the weak constraint case the TL and RP models are modified to include additional forcing terms on the right hand side of the model equations. These terms are needed to account for errors in the model dynamics. Inverse ROMS is tested in a realistic 3D baroclinic upwelling system with complex bottom topography, characterized by strong mesoscale eddy variability. We assimilate synthetic data for upper ocean (0-450 m) temperatures and currents over a period of 10 days using both a high resolution and a spatially and temporally aliased sampling array. During the assimilation period the flow field undergoes substantial changes from the initial state. This allows the inverse solution to extract the dynamically active information from the synthetic observations and improve the trajectory of the model state beyond the assimilation window. Both the strong and weak constraint assimilation experiments show forecast skill greater than persistence and climatology during the 10-20 days after the last observation is assimilated. Further investigation in the functional form of the model error covariance and in the use of the representer tangent linear model may lead to improvement in the forecast skill. (c) 2006 Elsevier Ltd. All rights reserved.

Di Lorenzo, E, Miller AJ, Neilson DJ, Cornuelle BD, Moisan JR.  2004.  Modelling observed California Current mesoscale eddies and the ecosystem response. International Journal of Remote Sensing. 25:1307-1312.   10.1080/01431160310001592229   AbstractWebsite

Satellite and in situ observations are used to test model dynamics for the California Current System (CCS). The model and data are combined to reconstruct the mesoscale ocean structure during a given three-week period. The resulting physical flow field is used to drive a 3D ecosystem model to interpret SeaWiFS and in situ chlorophyll-a (chl-a) variations. With this approach a more complete and consistent picture of the physical and ecosystem processes of the CCS is obtained, providing the basis for addressing fundamental questions about dynamics and predictability of the coastal ocean.