Pacific Coastal and Marine Science Center

Santa Cruz, CA, United States

Pacific Coastal and Marine Science Center

Santa Cruz, CA, United States
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Hegermiller C.A.,University of California at Santa Cruz | Hegermiller C.A.,Pacific Coastal and Marine Science Center | Antolinez J.A.A.,University of Cantabria | Rueda A.,University of Cantabria | And 5 more authors.
Journal of Physical Oceanography | Year: 2017

Characterization of wave climate by bulk wave parameters is insufficient for many coastal studies, including those focused on assessing coastal hazards and long-term wave climate influences on coastal evolution. This issue is particularly relevant for studies using statistical downscaling of atmospheric fields to local wave conditions, which are often multimodal in large ocean basins (e.g., Pacific Ocean). Swell may be generated in vastly different wave generation regions, yielding complex wave spectra that are inadequately represented by a single set of bulk wave parameters. Furthermore, the relationship between atmospheric systems and local wave conditions is complicated by variations in arrival time of wave groups from different parts of the basin. Here, this study addresses these two challenges by improving upon the spatiotemporal definition of the atmospheric predictor used in the statistical downscaling of local wave climate. The improved methodology separates the local wave spectrum into "wave families," defined by spectral peaks and discrete generation regions, and relates atmospheric conditions in distant regions of the ocean basin to local wave conditions by incorporating travel times computed from effective energy flux across the ocean basin. When applied to locations with multimodal wave spectra, including Southern California and Trujillo, Peru, the new methodology improves the ability of the statistical model to project significant wave height, peak period, and direction for each wave family, retaining more information from the full wave spectrum. This work is the base of statistical downscaling by weather types, which has recently been applied to coastal flooding and morphodynamic applications. © 2017 American Meteorological Society.

Helmuth B.,Northeastern University | Choi F.,Northeastern University | Matzelle A.,Northeastern University | Torossian J.L.,Northeastern University | And 59 more authors.
Scientific Data | Year: 2016

At a proximal level, the physiological impacts of global climate change on ectothermic organisms are manifest as changes in body temperatures. Especially for plants and animals exposed to direct solar radiation, body temperatures can be substantially different from air temperatures. We deployed biomimetic sensors that approximate the thermal characteristics of intertidal mussels at 71 sites worldwide, from 1998-present. Loggers recorded temperatures at 10-30 min intervals nearly continuously at multiple intertidal elevations. Comparisons against direct measurements of mussel tissue temperature indicated errors of ∼2.0-2.5 °C, during daily fluctuations that often exceeded 15°-20 °C. Geographic patterns in thermal stress based on biomimetic logger measurements were generally far more complex than anticipated based only on 'habitat-level' measurements of air or sea surface temperature. This unique data set provides an opportunity to link physiological measurements with spatially-and temporally-explicit field observations of body temperature. © 2016 The Author(s).

Gawehn M.,Unit of Marine and Coastal SystemsDeltaresDelft Netherlands | van Rooijen A.,Unit of Marine and Coastal SystemsDeltaresDelft Netherlands | Storlazzi C.D.,Pacific Coastal and Marine Science Center | Cheriton O.M.,Pacific Coastal and Marine Science Center | Reniers A.,Unit of Marine and Coastal SystemsDeltaresDelft Netherlands
Journal of Geophysical Research: Oceans | Year: 2016

Very low frequency (VLF, 0.001-0.005 Hz) waves are important drivers of flooding of low-lying coral reef-islands. In particular, VLF wave resonance is known to drive large wave runup and subsequent overwash. Using a 5 month data set of water levels and waves collected along a cross-reef transect on Roi-Namur Island in the Republic of the Marshall Islands, the observed VLF motions were categorized into four different classes: (1) resonant, (2) (nonresonant) standing, (3) progressive-growing, and (4) progressive-dissipative waves. Each VLF class is set by the reef flat water depth and, in the case of resonance, the incident-band offshore wave period. Using an improved method to identify VLF wave resonance, we find that VLF wave resonance caused prolonged (∼0.5-6.0 h), large-amplitude water surface oscillations at the inner reef flat ranging in wave height from 0.14 to 0.83 m. It was induced by relatively long-period, grouped, incident-band waves, and occurred under both storm and nonstorm conditions. Moreover, observed resonant VLF waves had nonlinear, bore-like wave shapes, which likely have a larger impact on the shoreline than regular, sinusoidal waveforms. As an alternative technique to the commonly used Fast Fourier Transformation, we propose the Hilbert-Huang Transformation that is more computationally expensive but can capture the wave shape more accurately. This research demonstrates that understanding VLF waves on reef flats is important for evaluating coastal flooding hazards. © 2016. American Geophysical Union.

Barnard P.L.,Pacific Coastal and Marine Science Center | van Ormondt M.,Deltares | Erikson L.H.,Pacific Coastal and Marine Science Center | Eshleman J.,National Park Service | And 4 more authors.
Natural Hazards | Year: 2014

The Coastal Storm Modeling System (CoSMoS) applies a predominantly deterministic framework to make detailed predictions (meter scale) of storm-induced coastal flooding, erosion, and cliff failures over large geographic scales (100s of kilometers). CoSMoS was developed for hindcast studies, operational applications (i.e., nowcasts and multiday forecasts), and future climate scenarios (i.e., sea-level rise + storms) to provide emergency responders and coastal planners with critical storm hazards information that may be used to increase public safety, mitigate physical damages, and more effectively manage and allocate resources within complex coastal settings. The prototype system, developed for the California coast, uses the global WAVEWATCH III wave model, the TOPEX/Poseidon satellite altimetry-based global tide model, and atmospheric-forcing data from either the US National Weather Service (operational mode) or Global Climate Models (future climate mode), to determine regional wave and water-level boundary conditions. These physical processes are dynamically downscaled using a series of nested Delft3D-WAVE (SWAN) and Delft3D-FLOW (FLOW) models and linked at the coast to tightly spaced XBeach (eXtreme Beach) cross-shore profile models and a Bayesian probabilistic cliff failure model. Hindcast testing demonstrates that, despite uncertainties in preexisting beach morphology over the ~500 km alongshore extent of the pilot study area, CoSMoS effectively identifies discrete sections of the coast (100s of meters) that are vulnerable to coastal hazards under a range of current and future oceanographic forcing conditions, and is therefore an effective tool for operational and future climate scenario planning. © 2014, Us Government.

Rueda A.,University of Cantabria | Camus P.,University of Cantabria | Tomas A.,University of Cantabria | Vitousek S.,Pacific Coastal and Marine Science Center | Mendez F.J.,University of Cantabria
Ocean Modelling | Year: 2016

Coastal floods often coincide with large waves, storm surge and tides. Thus, joint probability methods are needed to properly characterize extreme sea levels. This work introduces a statistical downscaling framework for multivariate extremes that relates the non-stationary behavior of coastal flooding events to the occurrence probability of daily weather patterns. The proposed method is based on recently-developed weather-type methods to predict extreme events (e.g., significant wave height, mean wave period, surge level) from large-scale sea-level pressure fields. For each weather type, variables of interest are modeled using Generalized Extreme Value (GEV) distributions and a Gaussian copula for modelling the interdependence between variables. The statistical dependence between consecutive days is addressed by defining a climate-based extremal index for each weather type. This work allows attribution of extreme events to specific weather conditions, enhancing the knowledge of climate-driven coastal flooding. © 2016 Elsevier Ltd

Barnard P.L.,Pacific Coastal and Marine Science Center | Erikson L.H.,Pacific Coastal and Marine Science Center | Kvitek R.G.,California State University, Monterey Bay
Geo-Marine Letters | Year: 2011

New multibeam echosounder and processing technologies yield sub-meter-scale bathymetric resolution, revealing striking details of bedform morphology that are shaped by complex boundary-layer flow dynamics at a range of spatial and temporal scales. An inertially aided post processed kinematic (IAPPK) technique generates a smoothed best estimate trajectory (SBET) solution to tie the vessel motion-related effects of each sounding directly to the ellipsoid, significantly reducing artifacts commonly found in multibeam data, increasing point density, and sharpening seafloor features. The new technique was applied to a large bedform field in 20-30 m water depths in central San Francisco Bay, California (USA), revealing bedforms that suggest boundary-layer flow deflection by the crests where 12-m-wavelength, 0.2-m-amplitude bedforms are superimposed on 60-m-wavelength, 1-m-amplitude bedforms, with crests that often were strongly oblique (approaching 90°) to the larger features on the lee side, and near-parallel on the stoss side. During one survey in April 2008, superimposed bedform crests were continuous between the crests of the larger features, indicating that flow detachment in the lee of the larger bedforms is not always a dominant process. Assessment of bedform crest peakedness, asymmetry, and small-scale bedform evolution between surveys indicates the impact of different flow regimes on the entire bedform field. This paper presents unique fine-scale imagery of compound and superimposed bedforms, which is used to (1) assess the physical forcing and evolution of a bedform field in San Francisco Bay, and (2) in conjunction with numerical modeling, gain a better fundamental understanding of boundary-layer flow dynamics that result in the observed superimposed bedform orientation. © 2011 Springer-Verlag (outside the USA).

Gallien T.W.,University of California at Irvine | Barnard P.L.,Pacific Coastal and Marine Science Center | Van Ormondt M.,Deltares | Foxgrover A.C.,Pacific Coastal and Marine Science Center | Sanders B.F.,University of California at Irvine
Journal of Coastal Research | Year: 2013

Coastal flood risk in California is concentrated around urbanized embayments that are protected by infrastructure, such as levees, pumps, and flood walls, which pose a challenge to accurate flood prediction. A capability to predict coastal urban flooding at the parcel-scale (individual home or street) from high ocean levels (extreme high tides) is shown here by coupling a regional ocean forecasting system to an embayment-scale hydrodynamic model that incorporates detailed information about flood defenses. A unique flooding data set affords the rare opportunity to validate model predictions and allows us to identify model data that are essential for accurate forecasting. In particular, results show that flood defense height data are critical, and here, that information is supplied by a Real Time Kinematic Global Positioning System (RTK-GPS) survey, which yields ca. 1-cm, vertical root mean-squared error accuracy. Bathymetry surveys and aerial Light Detection and Ranging (LIDAR) data characterizing the embayment also prove essential. Moreover, hydrodynamic modeling of flood inundation is shown to significantly improve on planar surface models, which overestimate inundation, particularly when manipulated to account for run-up in a simplistic way. This is attributed to the transient nature of overtopping flows and motivates the need for dynamic, spatially-distributed overtopping models that are tailored to the urban environment. © 2012, the Coastal Education & Research Foundation.

Alvarez J.A.A.,University of Cantabria | Mendez F.J.,University of Cantabria | Camus P.,University of Cantabria | Vitousek S.,Pacific Coastal and Marine Science Center | And 3 more authors.
Journal of Geophysical Research: Oceans | Year: 2016

Interest in understanding long-term coastal morphodynamics has recently increased as climate change impacts become perceptible and accelerated. Multiscale, behavior-oriented and process-based models, or hybrids of the two, are typically applied with deterministic approaches which require considerable computational effort. In order to reduce the computational cost of modeling large spatial and temporal scales, input reduction and morphological acceleration techniques have been developed. Here we introduce a general framework for reducing dimensionality of wave-driver inputs to morphodynamic models. The proposed framework seeks to account for dependencies with global atmospheric circulation fields and deals simultaneously with seasonality, interannual variability, long-term trends, and autocorrelation of wave height, wave period, and wave direction. The model is also able to reproduce future wave climate time series accounting for possible changes in the global climate system. An application of long-term shoreline evolution is presented by comparing the performance of the real and the simulated wave climate using a one-line model. © 2015. American Geophysical Union.

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