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The approach for modeling bioluminescence (BL) potential is proposed. The approach consists of (1) estimation of the adjoint (by backward in time integration of the adjoint model), (2) generation of ensembles of BL potential initial conditions and source minus sink term, and (3) estimation of two integrals: the integration of the adjoint with the BL potential initial conditions and the integration of the adjoint with the BL potential source minus sink term. In this case, the impact of physical processes on BL potential dynamics is introduced through the one backward integration of the adjoint. The proposed approach has been applied to modeling of the BL potential changes in the area of the submesoscale filament, which developed during the upwelling event in the Monterey Bay area, California. Comparisons of modeled histograms with those observed show that predicted changes in mean BL potential values in the area of filament very closely resemble the observed ones: increase over 5 days in mean BL potential values in the top 15 m and decrease in mean BL potential values between 30 and 45 m depth in the area of the filament. There is a similar good qualitative and quantitative agreement between observed and model-predicted differences in histograms when BL potential values in 30–45 m depth are compared to the BL potential values in the top 15 m. [ABSTRACT FROM AUTHOR]

Vessel-based light detection and ranging (LIDAR) was employed to collect coastal topography data and to quantify the rates of erosion and spatial distribution of coastal retreat around Monterey Bay, California during the 2008-09 (non-El Ni ˜no) and 2009-10 El Ni ˜no. These data were compared with pre/post-El Ni ˜no LIDAR data from 1997-98 to assess shoreline change and to test the following hypotheses: (1) that broad-scale (km) spatial distribution of erosion rates is positively correlated with wave energy, and (2) that fine-scale erosion hot spots (segments of the coastline exhibiting considerably higher rates of erosion than adjacent areas) shift at predictable alongshore wavelengths between consecutive El Ni ˜ no and inter-El Ni ˜no periods. Broad-scale erosion was found to be significantly higher during the 2009-10 El Ni ˜ no vs. the 2008-09 non-El Ni ˜no period in both the south (1.8 m vs. 0.1 m average) and north bays (0.5 m vs. 0.0 m average). The broad-scale distribution of erosion rates during the 2009-10 El Ni ˜no was positively correlated with wave energy. In southern Monterey Bay, erosion rates increased along a wave energy gradient from south to north, whereas erosion and wave energy were both focused and highest at a single location in the northern bay. Fine-scale erosion hot spots were found to occur during the 1997-98 and 2009-10 El Ni ˜ no and the 1998-08 inter-El Ni ˜no period. These hot spots were found to be significantly correlated at −160 m during the 1997- 98 El Ni ˜no to 1998-2009 inter-El Ni ˜no periods and 100 m during the 1998-2009 inter-El Ni ˜no to 2009-10 El Ni ˜no periods in southern Monterey Bay. Hot spots that occurred during one El Ni ˜ no or inter-El Ni ˜no period shifted spatially alongshore during the subsequent El Ni ˜ no or inter-El Ni ˜no period. Vessel-based LIDAR proved to be effective for detecting coastal change at high spatial resolutions and revealing fine-scale patterns of shoreline retreat. [ABSTRACT FROM AUTHOR]

Abstract: Impact of HF radar surface-current assimilation on ocean circulation model predictions in the Monterey Bay area is studied and evaluated during the time frame of the Autonomous Ocean Sampling Network (AOSN-II) experiment (August–September 2003). In the first instance, a previously described method for assimilation of surface current data is applied to 33-h low-pass-filtered data and a non-tidal version of the circulation model. It is demonstrated that assimilation of surface velocity data significantly improves the surface and subsurface correlation of model currents with moored current observations. These results from the AOSN-II period illustrate that surface-current assimilation is beneficial even in cases for which very high-resolution (3km) atmospheric forcing is utilized. The assimilation approach is also tested with hourly, unfiltered, CODAR-type HF radar-derived surface currents within a model configuration that includes tidal forcing. It is shown, that assimilation of unfiltered (with tides) surface-current observations into the model with tides improves the sub-tidal model predictions to the level comparable with the assimilation of filtered data into the non-tidal model, which is significant with respect to options for designing real-time nowcast and forecast systems. Finally, the approach is extended and evaluated for the direct assimilation of HF radar-derived radial velocity components. The model runs that included assimilation of radials from at least two HF radar sites show better correlations with observations than the non-assimilative run, especially those runs that included radials from the Santa Cruz site. Directions of radials for that site coincide with the directions of dominant southward flow during upwelling events and the northward flow during relaxation events. Direct assimilation of radial currents extends the range of influence of the data into regions covered by only one HF radar site. [Copyright &y& Elsevier]

Abstract: Glider observations were essential components of the observational program in the Autonomous Ocean Sampling Network (AOSN-II) experiment in the Monterey Bay area during summer of 2003. This paper is focused on the impact of the assimilation of glider temperature and salinity observations on the Navy Coastal Ocean Model (NCOM) predictions of surface and subsurface properties. The modeling system consists of an implementation of the NCOM model using a curvilinear, orthogonal grid with 1–4km resolution, with finest resolution around the bay. The model receives open boundary conditions from a regional (9km resolution) NCOM implementation for the California Current System, and surface fluxes from the Coupled Ocean–Atmosphere Mesoscale Prediction System (COAMPS) atmospheric model at 3km resolution. The data assimilation component of the system is a version of the Navy Coupled Ocean Data Assimilation (NCODA) system, which is used for assimilation of the glider data into the NCOM model of the Monterey Bay area. The NCODA is a fully 3D multivariate optimum interpolation system that produces simultaneous analyses of temperature, salinity, geopotential, and vector velocity. Assimilation of glider data improves the surface temperature at the mooring locations for the NCOM model hindcast and nowcasts, and for the short-range (1–1.5 days) forecasts. It is shown that it is critical to have accurate atmospheric forcing for more extended forecasts. Assimilation of glider data provided better agreement with independent observations (for example, with aircraft measured SSTs) of the model-predicted and observed spatial distributions of surface temperature and salinity. Mooring observations of subsurface temperature and salinity show sharp changes in the thermocline and halocline depths during transitions from upwelling to relaxation and vice versa. The non-assimilative run also shows these transitions in subsurface temperature; but they are not as well defined. For salinity, the non-assimilative run significantly differs from the observations. However, the glider data assimilating run is able to show comparable results with observations of thermocline as well as halocline depths during upwelling and relaxation events in the Monterey Bay area. It is also shown that during the relaxation of wind, the data assimilative run has higher value of subsurface velocity complex correlation with observations than the non-assimilative run. [Copyright &y& Elsevier]