Øyvind Breivik

Real time assimilation of HF radar currents into a coastal ocean model

Abstract A real time assimilation and forecasting system for coastal currents is presented. The purpose of the system is to deliver current analyses and forecasts on based on assimilation of high-frequency radar surface current measurements. The local Vessel Traffic Service monitoring the ship traffic to two oil terminals on the coast of Norway received the analyses and forecasts in real time. A new assimilation method based on optimal interpolation is presented where spatial covariances derived from an ocean model are used instead of simplified mathematical formulations. An array of high frequency radar antennae provides the current measurements. A suite of nested ocean models comprises the model system. The observing system is found to yield good analyses and short range forecasts that are significantly improved compared to a model twin without assimilation. The system is fast, analysis and 6-h forecasts are ready at the Vessel Traffic Service 45 min after acquisition of radar measurements.

Wind-induced drift of objects at sea: The leeway field method

A method for conducting leeway field experiments to establish the drift properties of small objects (0.1–25 m) is described. The objective is to define a standardized and unambiguous procedure for condensing the drift properties down to a set of coefficients that may be incorporated into existing stochastic trajectory forecast models for drifting objects of concern to search and rescue operations and other activities involving vessels lost at sea such as containers with hazardous material. An operational definition of the slip or wind and wave-induced motion of a drifting object relative to the ambient current is proposed. This definition taken together with a strict adherence to a 10 m wind speed allows us to refer unambiguously to the leeway of a drifting object. We recommend that all objects if possible be studied using what we term the direct method, where the object’s leeway is studied directly using an attached current meter. We establish a minimum set of parameters that should be estimated for a drifting object for it to be included in the operational forecast models used for prediction of search areas for drifting objects. We divide drifting objects into four categories, depending on their size. For the smaller objects (less than 0.5 m), an indirect method of measuring the object’s motion relative to the ambient current must be used. For larger objects, direct measurement of the motion through the near-surface water masses is strongly recommended. Larger objects are categorized according to the ability to attach current meters and wind monitoring systems to them. The leeway field method proposed here is illustrated with results from field work where three objects were studied in their distress configuration; a 1:3.3 sized model of a 40-foot Shipping container, a World War II mine and a 220 l (55-gallon) oil drum.

Surface wave effects in the NEMO ocean model: Forced and coupled experiments

The NEMO general circulation ocean model is extended to incorporate three physical processes related to ocean surface waves, namely the surface stress (modified by growth and dissipation of the oceanic wave field), the turbulent kinetic energy flux from breaking waves, and the Stokes-Coriolis force. Experiments are done with NEMO in ocean-only (forced) mode and coupled to the ECMWF atmospheric and wave models. Ocean-only integrations are forced with fields from the ERA-Interim reanalysis. All three effects are noticeable in the extra-tropics, but the sea-state dependent turbulent kinetic energy flux yields by far the largest difference. This is partly because the control run has too vigorous deep mixing due to an empirical mixing term in NEMO. We investigate the relation between this ad hoc mixing and Langmuir turbulence and find that it is much more effective than the Langmuir parameterization used in NEMO. The biases in sea surface temperature as well as subsurface temperature are reduced, and the total ocean heat content exhibits a trend closer to that observed in a recent ocean reanalysis (ORAS4) when wave effects are included. Seasonal integrations of the coupled atmosphere-wave-ocean model consisting of NEMO, the wave model ECWAM and the atmospheric model of ECMWF similarly show that the sea surface temperature biases are greatly reduced when the mixing is controlled by the sea state and properly weighted by the thickness of the uppermost level of the ocean model. These wave-related physical processes were recently implemented in the operational coupled ensemble forecast system of ECMWF.

Wave Extremes in the Northeast Atlantic

AbstractThe objective of this study is to compute 100-yr return value estimates of significant wave height using a new hindcast developed by the Norwegian Meteorological Institute. This regional hindcast covers the northeast Atlantic and spans the period 1958–2009.The return value estimates are based upon three different stationary models commonly applied in extreme value statistics: the generalized extreme value (GEV) distribution, the joint GEV distribution for the r largest-order statistic (rLOS), and the generalized Pareto (GP) distribution. Here, the qualitative differences between the models and their corresponding confidence intervals are investigated.

Forecasting the Drift of Objects and Substances in the Ocean

Forecasting the drift of floating objects, ships and oil spills is an important ocean application. Most nations support services for ship safety, oil spill combatment and search-and-rescue, all of which may benefit from drift forecasts. Examples from Norwegian services are discussed. The models for drifting things themselves are founded on hydrodynamic principles (ship drift), empirical parameterizations (floating objects) and oil-water chemistry. An overview of these models is given. All the drift models share a crucial reliance on geophysical forcing data. In operational services, these data are obtained from weather, wave and ocean forecast models. Currently, ocean forecasts are the component with greatest scope for improvement. Effective interfacing of drift forecasting services to the users - the emergency response services - is vital for obtaining optimal benefit from the forecasts.

Approximate Stokes Drift Profiles in Deep Water

AbstractA deep-water approximation of the Stokes drift velocity profile is explored as an alternative to the monochromatic profile. The alternative profile investigated relies on the same two quantities required for the monochromatic profile, namely, the Stokes transport and the surface Stokes drift velocity. Comparisons with parametric spectra and profiles under wave spectra from the Interim ECMWF Re-Analysis (ERA-Interim) and buoy observations reveal much better agreement than the monochromatic profile even for complex sea states. That the profile gives a closer match and a more correct shear has implications for ocean circulation models since the Coriolis–Stokes force depends on the magnitude and direction of the Stokes drift profile, and Langmuir turbulence parameterizations depend sensitively on the shear of the profile. The alternative profile comes at no added numerical cost compared to the monochromatic profile.

Advances in search and rescue at sea

A topical collection on “Advances in Search and Rescue at Sea” has appeared in recent issues of Ocean Dynamics following the latest in a series of workshops on “Technologies for Search and Rescue and other Emergency Marine Operations” (2004, 2006, 2008, and 2011), hosted by IFREMER in Brest, France. Here, we give a brief overview of the history of search and rescue at sea before we summarize the main results of the papers that have appeared in the topical collection.

A short-term predictive system for surface currents from a rapidly deployed coastal HF radar network

In order to address the need for surface trajectory forecasts following deployment of coastal HF radar systems during emergency-response situations (e.g., search and rescue, oil spill), a short-term predictive system (STPS) based on only a few hours data background is presented. First, open-modal analysis (OMA) coefficients are fitted to 1-D surface currents from all available radar stations at each time interval. OMA has the effect of applying a spatial low-pass filter to the data, fills gaps, and can extend coverage to areas where radial vectors are available from a single radar only. Then, a set of temporal modes is fitted to the time series of OMA coefficients, typically over a short 12-h trailing period. These modes include tidal and inertial harmonics, as well as constant and linear trends. This temporal model is the STPS basis for producing up to a 12-h current vector forecast from which a trajectory forecast can be derived. We show results of this method applied to data gathered during the September 2010 rapid-response demonstration in northern Norway. Forecasted coefficients, currents, and trajectories are compared with the same measured quantities, and statistics of skill are assessed employing 16 24-h data sets. Forecasted and measured kinetic variances of the OMA coefficients typically agreed to within 10–15%. In one case where errors were larger, strong wind changes are suspected and examined as the cause. Sudden wind variability is not included properly within the STPS attack we presently employ and will be a subject for future improvement.

A Stokes drift approximation based on the Phillips spectrum

Abstract A new approximation to the Stokes drift velocity profile based on the exact solution for the Phillips spectrum is explored. The profile is compared with the monochromatic profile and the recently proposed exponential integral profile. ERA-Interim spectra and spectra from a wave buoy in the central North Sea are used to investigate the behavior of the profile. It is found that the new profile has a much stronger gradient near the surface and lower normalized deviation from the profile computed from the spectra. Based on estimates from two open-ocean locations, an average value has been estimated for a key parameter of the profile. Given this parameter, the profile can be computed from the same two parameters as the monochromatic profile, namely the transport and the surface Stokes drift velocity.

Wind and wave extremes over the world oceans from very large ensembles

Global return values of marine wind speed and significant wave height are estimated from very large aggregates of archived ensemble forecasts at +240 h lead time. Long lead time ensures that the forecasts represent independent draws from the model climate. Compared with ERA-Interim, a reanalysis, the ensemble yields higher return estimates for both wind speed and significant wave height. Confidence intervals are much tighter due to the large size of the data set. The period (9 years) is short enough to be considered stationary even with climate change. Furthermore, the ensemble is large enough for nonparametric 100 year return estimates to be made from order statistics. These direct return estimates compare well with extreme value estimates outside areas with tropical cyclones. Like any method employing modeled fields, it is sensitive to tail biases in the numerical model, but we find that the biases are moderate outside areas with tropical cyclones.