Evaluation of bio-optical inversion of spectral irradiance measured from an autonomous underwater vehicle

Autonomous underwater vehicles (AUVs) can map water conditions at high spatial (horizontal and vertical) and temporal resolution, including under cloudy conditions when satellite and airborne remote sensing are not feasible. As part of the RADYO program, we deployed a passive radiometer on an AUV in the Santa Barbara Channel and off the coast of Hawaii to apply existing bio-optical algorithms for characterizing the optical constituents of coastal seawater (i.e., dissolved organic material, algal biomass, and other particles). The spectral differences between attenuation coefficients were computed from ratios of downwelling irradiance measured at depth and used to provide estimates of the in-water optical constituents. There was generally good agreement between derived values of absorption and concurrent measurements of this inherent optical property in Santa Barbara Channel. Wave focusing, cloud cover, and low attenuation coefficients influenced results off the coast of Hawaii and are used to evaluate the larger-scale application of these methods in the near surface coastal oceans

Evaluating Connectivity between Marine Protected Areas Using CODAR High-Frequency Radar

To investigate the connectivity between central California marine protected areas (MPAs), back-projections were calculated using the network of high-frequency (HF) radar ocean surface current mapping stations operated along the California coast by the member institutions of the Coastal Ocean Currents Monitoring Program with funding provided by California voters through Propositions 40 & 50 and administered by the State Coastal Conservancy. Trajectories of 1 km resolution grids of water particles were back-projected from ten MPAs each hour, out through 40 days in the past, from each day in 2008, producing a map of where surface waters travel over a 40-day period to reach the MPAs - and visualizations of the length of time the waters travel along these paths. By comparing the travel times of those back-projected track-points that crossed between MPA regions, the connection time between MPAs along the State\u27s central coast was assessed. Repeating these calculations resulted in a connectivity matrix between the MPAs in the region, and may be useful for assessing connectivity for the important invertebrate and fish larvae that are restricted to the surface ocean during a fraction of their lifecycle

An empirical statistical model relating winds and ocean surface currents : implications for short-term current forecasts

An empirical statistical model is developed that relates the non-tidal motion of the ocean surface currents off the Oregon coast to forecasts of the coastal winds. The empirical statistical model is then used to produce predictions of the surface currents that are evaluated for their agreement with measured currents. Measurements of the ocean surface currents were made at 6 km resolution using Long-Range CODAR SeaSonde high-frequency (HF) surface current mappers and wind forecasts were provided at 12 km resolution by the North American Mesoscale (NAM) model. First, the response of the surface currents to wind-forcing measured by five coastal National Data Buoy Center (NDBC) stations was evaluated using empirical orthogonal function (EOF) analysis. A significant correlation of approximately 0.8 was found between the majority of the variability in the seasonal anomalies of the low-pass filtered surface currents and the seasonal anomalies of the low-pass filtered wind stress measurements. The U and the V components of the measured surface currents were both shown to be forced by the zonal and meridional components of the wind-stress at the NDBC stations. Next, the NAM wind forecasts were tested for agreement with the measurements of the wind at the NDBC stations. Significant correlations of around 0.8 for meridional wind stress and 0.6 for zonal wind stress were found between the seasonal anomalies of the low-pass filtered wind stress measured by the NDBC stations and the seasonal anomalies of the low-pass filtered wind stress forecast by the NAM model. Given the amount of the variance in the winds captured by the NAM model and the response of the ocean surface currents to both components of the wind, bilinear regressions were formed relating the seasonal anomalies of the low-pass filtered NAM forecasts to the seasonal anomalies of the low-pass filtered surface currents. The regressions turned NAM wind forecasts into predictions of the seasonal anomalies of the low-pass filtered surface currents. Calculations of the seasonal cycle in the surface currents, added to these predicted seasonal anomalies, produced a non-tidal estimation of the surface currents that allowed a residual difference to be calculated from recent surface current measurements. The sum of the seasonal anomalies, the seasonal cycle, and the residual formed a prediction of the non-tidal surface currents. The average error in this prediction of the surface currents off the Oregon coast remained less than 4 cm/s out through 48 hours into the future.Keywords: Current, physical, Oceanography, Forecast, Low-pass filtered, Radio, Mapping, NASA, Coastal, Bilinear, High-frequency (HF) radar, Seasonal, Stress, Marine, Ocean, NSF, regressions, Buoy, COAS, surface, NAM, Predict, Wind, Empirical, Oregon, CODAR, EOF, Statistical, Kosro, GLOBE

Integrated measurements of acoustical and optical thin layers II: Horizontal length scales

The degree of layered organization of planktonic organisms in coastal systems impacts trophic interactions, the vertical availability of nutrients, and many biological rate processes. While there is reasonable characterization of the vertical structure of these phenomena, the extent and horizontal length scale of variation has rarely been addressed. Here we extend the examination of the vertical scale in the first paper of the series to the horizontal scale with combined shipboard acoustic measurements and bio-optic measurements taken on an autonomous underwater vehicle. Measurements were made in Monterey Bay, CA from 2002 to 2008 for the bio-optical parameters and during 2006 for acoustic scattering measurements. The combined data set was used to evaluate the horizontal decorrelation length scales of the bio-optical and acoustic scattering layers themselves. Because biological layers are often decoupled from the physical structure of the water column, assessment of the variance within identified layers was appropriate. This differs from other studies in that physical parameters were not used as a basis for the layer definition. There was a significant diel pattern to the decorrelation length scale for acoustic layers with the more abundant nighttime layers showing less horizontal variability despite their smaller horizontal extent. A significant decrease in the decorrelation length scale was found in bio-optical parameters over six years of study, coinciding with a documented shift in the plankton community. Results highlight the importance of considering plankton behavior and time of day with respect to scale when studying layers, and the challenges of sampling these phenomena

Progress in Operational Modeling in Support of Oil Spill Response

Following the 2010 Deepwater Horizon accident of a massive blow-out in the Gulf of Mexico, scientists from government, industry, and academia collaborated to advance oil spill modeling and share best practices in model algorithms, parameterizations, and application protocols. This synergy was greatly enhanced by research funded under the Gulf of Mexico Research Initiative (GoMRI), a 10-year enterprise that allowed unprecedented collection of observations and data products, novel experiments, and international collaborations that focused on the Gulf of Mexico, but resulted in the generation of scientific findings and tools of broader value. Operational oil spill modeling greatly benefited from research during the GoMRI decade. This paper provides a comprehensive synthesis of the related scientific advances, remaining challenges, and future outlook. Two main modeling components are discussed: Ocean circulation and oil spill models, to provide details on all attributes that contribute to the success and limitations of the integrated oil spill forecasts. These forecasts are discussed in tandem with uncertainty factors and methods to mitigate them. The paper focuses on operational aspects of oil spill modeling and forecasting, including examples of international operational center practices, observational needs, communication protocols, and promising new methodologies

Progress in Operational Modeling in Support of Oil Spill Response

Following the 2010 Deepwater Horizon accident of a massive blow-out in the Gulf of Mexico, scientists from government, industry, and academia collaborated to advance oil spill modeling and share best practices in model algorithms, parameterizations, and application protocols. This synergy was greatly enhanced by research funded under the Gulf of Mexico Research Initiative (GoMRI), a 10-year enterprise that allowed unprecedented collection of observations and data products, novel experiments, and international collaborations that focused on the Gulf of Mexico, but resulted in the generation of scientific findings and tools of broader value. Operational oil spill modeling greatly benefited from research during the GoMRI decade. This paper provides a comprehensive synthesis of the related scientific advances, remaining challenges, and future outlook. Two main modeling components are discussed: Ocean circulation and oil spill models, to provide details on all attributes that contribute to the success and limitations of the integrated oil spill forecasts. These forecasts are discussed in tandem with uncertainty factors and methods to mitigate them. The paper focuses on operational aspects of oil spill modeling and forecasting, including examples of international operational center practices, observational needs, communication protocols, and promising new methodologies