A moving static pressure distribution is commonly used to simulate a travelling ship. However, the ship movement changes the fluid velocity around the hull, inducing pressures on the hull surface that are no longer equal to the static pressure. Therefore, we introduce a dynamic pressure correction strategy, which can accurately simulate the impact of the ship movement on the hull-surface pressure and preserve the desired hull shape under both stationary and transient conditions. The strategy is applied to a high-order spectral model and used to investigate ship-induced waves and wave resistance over a both flat and variable topography. We explore various parameters in our study, including the average water depth to ship draft ratio (h(0)/d), the channel width to ship width ratio (W/B), the Froude number (Fr-0 = U/root gh(0)) and variations in bathymetric slope. Compared with experiments on a flat bottom, the numerical results with dynamic correction show better accuracy in the simulation of ship-induced waves and wave resistance than those obtained using a static pressure distribution. The correlation coefficient for wake waves between the numerical and experimental results is improved by approximately 0.25 with the dynamic correction strategy. The amplitude and wavelength of ship-induced mini-tsunamis over a variable topography are found to be reduced when employing a dynamic correction compared with a static pressure distribution, and this effect becomes more pronounced with higher Froude number. The static pressure approach is shown to allow large deformations of the desired hull shape and changes in ship volume which are responsible for the different wave patterns from the two approaches.
This paper presents an assessment of three methods used for sea state estimation via the wave buoy analogy, where measured ship responses are processed. The three methods all rely on Machine Learning exclusively but they have different output; Method 1 provides bulk parameters, Method 2 yields a point wave spectrum and the wave direction, while Method 3 gives the directional wave spectrum in non-parametric form. The assessment is made using full-scale data from an in-service container ship in cross-Atlantic service. Training and testing of the methods are made using data from a wave radar, and the three methods perform well. An uncertainty measure, equivalently, a trust level indicator, based on the variation between the post-processed outputs of the methods is proposed, and this facilitates determination of estimates with small errors; without knowing the ground truth.
Ocean monitoring will improve outcomes if ways of knowing and priorities from a range of interest groups are successfully integrated. Coastal Indigenous communities hold unique knowledge of the ocean gathered through many generations of inter-dependent living with marine ecosystems. Experiences and observations from living within that system have generated ongoing local and traditional ecological knowledge (LEK and TEK) and Indigenous knowledge (IK) upon which localized sustainable management strategies have been based. Consequently, a comprehensive approach to ocean monitoring should connect academic practices (“science”) and local community and Indigenous practices, encompassing “TEK, LEK, and IK.” This paper recommends research approaches and methods for connecting scientists, local communities, and IK holders and their respective knowledge systems, and priorities, to help improve marine ecosystem management. Case studies from Canada and New Zealand (NZ) highlight the emerging recognition of IK systems in natural resource management, policy and economic development. The in-depth case studies from Ocean Networks Canada (ONC) and the new Moana Project, NZ highlight real-world experiences connecting IK with scientific monitoring programs. Trial-tested recommendations for successful collaboration include practices for two-way knowledge sharing between scientists and communities, co-development of funding proposals, project plans and educational resources, mutually agreed installation of monitoring equipment, and ongoing sharing of data and research results. We recommend that future ocean monitoring research be conducted using cross-cultural and/or transdisciplinary approaches. Vast oceans and relatively limited monitoring data coupled with the urgency of a changing climate emphasize the need for all eyes possible providing new data and insights. Community members and ocean monitoring scientists in joint research teams are essential for increasing ocean information using diverse methods compared with previous scientific research. Research partnerships can also ensure impactful outcomes through improved understanding of community needs and priorities.
Temperature data 1900–2010 from meteorological stations across the world have been analyzed and it has been found that all land areas generally have two different valid temperature trends. Coastal stations and hill stations facing ocean winds are normally more warm-trended than the valley stations that are sheltered from dominant oceans winds.
Thus, we found that in any area with variation in the topography, we can divide the stations into the more warm trended ocean air-affected stations, and the more cold-trended ocean air-sheltered stations. We find that the distinction between ocean air-affected and ocean air-sheltered stations can be used to identify the influence of the oceans on land surface. We can then use this knowledge as a tool to better study climate variability on the land surface without the moderating effects of the ocean.
We find a lack of warming in the ocean air sheltered temperature data – with less impact of ocean temperature trends – after 1950. The lack of warming in the ocean air sheltered temperature trends after 1950 should be considered when evaluating the climatic effects of changes in the Earth’s atmospheric trace amounts of greenhouse gasses as well as variations in solar conditions.