EARTH SCIENCE > OCEANS > OCEAN WAVES > WAVE HEIGHT
Type of resources
Topics
Keywords
Contact for the resource
Provided by
-
Metadata record for data from ASAC Project 2315 See the link below for public details on this project. ---- Public Summary from Project ---- Project title: EFFECTS OF THE MODULATION OF THE SURFACE SHEAR STRESS BY THE WAVE FIELD IN A MODEL OF THE SOUTHERN OCEAN This project will investigate the sensitivity of currents and tracer properties in a non-eddy-resolving ocean general circulation model to a formulation of the surface shear stress which takes account of surface air and water velocities induced by the ocean wave field. These velocities will be computed accurately from archived model wave fields and also parameterised from wind and current velocities. From the abstract of the reference paper: We present a basic analysis of the propagation of deep-water waves on curved trajectories. The key feature is that the amplitude of the wave varies transversely, and may in the generation of a short-crested of high amplitude. The properties of there waves are explored, and it is suggested that they are a model for extreme waves, which may violate the conditions under which the classical distribution of wave heights has been derived. In their full development, they are manifested a generic rouge waves. From the 2002/2003 season: The aim of this project was to investigate mode water formation south of Australia in an ocean general circulation model (OGCM). The grant monies were used to employ a numerical modeller (Dr Harun Rashid) who became familiar with the curvilinear grid version of the modular ocean model No. 1 (MOM1) model developed by Ross Murray, and then applied the model with high resolution (0.6 x 0.4 degree) in the region south-west of Tasmania, where recent observations obtained on Franklin cruise (Fr9801) to the west of the SR3 section, indicated that mode water was being formed. The model was found to be inadequate to the task of simulating the formation region, as also were the OCCAM simulations, which have been downloaded and compared with the MOM1 simulations. The reason for this negative conclusion was sought during the course of the project, and it was determined that in the OGCMs: (a) the westward advection south of Tasmania was too strong, and (b) the coefficients of lateral diffusion at deeper levels in the water column were too large. The cruise data, which were investigated by Paul Barker as part of his Ph.D. thesis, indicated that the region of water mass formation south-west of Tasmania, occurs over the depth range of the mode water and the intermediate water and through to the upper circumpolar deep water (300 - 1500 m). It was deduced that the formation mechanism involves the mixing of two source waters, one from the Tasman Sea, the other from the Southern Ocean, which combine to form Tasmanian Subantarctic Mode Water (TSAMW), Tasmanian Intermediate Water (TIW), and probably Tasmanian Upper Circumpolar Deep Water (TUCDW). The dynamical reason for the location of the water mass formation appears to be the existence of a saddlepoint in the streamflow (at which the mean horizontal velocity is zero) over the depth range (300 - 1500m), due to the gyral circulation of the South Australian Basin to the west and the retroflection of the Tasman Outflow to the east. In order to represent this physics, it is very important to simulate correctly the advection at each level in the water column This is not done by the OGCMs, but in the course of the project, the importance of advection on the position of the saddlepoint was demonstrated in a series of simulations using the transports obtained from a simple Sverdrup transport model. The modelled fields were then used to advect temperature and salinity at each level with lateral diffusion coefficients adjusted for the best match with the observed property fields. These 'best fit' lateral diffusion coefficients in the deeper levels were found to be much smaller than those used in the OGCMs. The mechanism outlined above is distinct from that in earlier work in which mode water formation was interpreted using Ekman rather then gyral dynamics, without attention being given to the deeper levels. A simple balance shows that the gyral current is of similar magnitude to the Ekman current in the surface layer, and below the surface layer the Ekman current is absent. Recently (December 2003) Ross Murray has indicated that the problem addressed in this 2002-2003 grant can be revisited, using a 20 year simulation he is obtaining with TPAC NCEP II forcing on a resolution of 1/8 degree. It is our intention to work with Ross in February 2004 to see if the problems detailed above can be overcome, so that the ocean physics in this important water mass formation region can be simulated.
-
Between 07:00 and 08:00 UTC on the 4th July 2017, the South African icebreaker S.A. Agulhas II entered the Antarctic MIZ (62 South and 30 East) during an explosive polar cyclone. A system of two GigE monochrome industrial CMOS cameras with a 2/3 inch sensor was installed on the icebreaker. The cameras provide a field of view of the ocean surface around the port side of the ship. Images were recorded with resolution 2448x2048 pixels and a sampling rate 2 Hz during daylight on the 4th July 2017. The wave acquisition stereo-camera system (WASS; https://www.dais.unive.it/wass/) is used to reconstruct the water surface elevation. Reconstructed surface elevations are given as .nc files (6). The file name is “wass__20170704_hhmm.nc” where hh and mm denote the hour and minute in UTC of the start of each acquisition. X_grid and Y_grid are the grid in x and y direction, resolution 1000mm or 1m. Fps is the acquisition frequency, resolution 2Hz. Time is a dummy variable, time is reconstructed from start time and fps. Z is the surface elevation in space and time, in mm. Missing values are "Nan". Other variables are WASS control variables. Further details on the measurements and use of the data can be found at Alberello et al. “An extreme wave field in the winter Antarctic marginal ice zone during an explosive polar cyclone”.
-
Reconstructed nonlinear surface from WAMOS (marine radar) data collected during the 3rd leg of Antarctic Circumnavigation Expedition, from the end of January to the end of March 2017. WAMOS data (AAS_4434_ACE_WAMOS) are processed with the Higher Order Spectral Method (HOSM) to provide the nonlinear surface elevation and the corresponding spectrum of waves during ACE. A Montecarlo approach is adopted to reproduce the natural variability of the sea state and gain reliable statistics of the underlying nonlinear surface elevation. Details on the method can be found on Toffoli, Alessandro, et al. "Evolution of weakly nonlinear random directional waves: laboratory experiments and numerical simulations." Journal of Fluid Mechanics 664 (2010): 313-336. File structure: Folder name corresponds to the time stamp of the input spectrum (yyyyMMddhhmmss) from AAS_4434_ACE_WAMOS. Each folder contains: 1. The surface elevation for 250 random realisations at 10 instant in times from initialisation saved every 5 dominant wave periods apart (0,5,10,15,…,50 Tp). The ten digits name is structured as 0000NRRttt where NRR is the number of the random realisation (from 1 to 250) and ttt denotes the time index (from 0 to 10). 2. NEW_SPECTRUM.DAT the 2D spectrum (64x64) as a columnar vector of the initial spectrum read from the AAS_4434_ACE_WAMOS. 3. INPUT_SPECTRUM.DAT the 2D spectrum (256x256) as a columnar vector of the initial spectrum for the HOSM. 4. WAVENUMBERSX.DAT and WAVENUMBERSY.DAT the wavenumber in x and y respectively 5. PP_INFO.DAT contains the peak period (Tp) in seconds 6. RUN_INFO.DAT contains the resolution in x of the WAMOS spectrum (64), the resolution in y of the WAMOS spectrum (64), the delta x for the surface elevation in m, the delta y for the surface elevation in m. Subsequent parameters are flags for the HOSM method. Waves in the Southern Ocean are the biggest on the planet. They exert extreme stresses on the coastline of the Sub-Antarctic Islands, which affects coastal morphology and the delicate natural environment that the coastline offers. In Antarctic waters, the sea ice cover reflects a large proportion of the wave energy, creating a complicated sea state close to the ice edge. The remaining proportion of the wave energy penetrates deep into the ice-covered ocean and breaks the ice into relatively small floes. Then, the waves herd the floes and cause them to collide and raft. There is a lack of field data in the Sub-Antarctic and Antarctic Oceans. Thus, wave models are not well calibrated and perform poorly in these regions. Uncertainties relate to the difficulties to model the strong interactions between waves and currents (the Antarctic Circumpolar and tidal currents) and between waves and ice (reflected waves modify the incident field and ice floes affect transmission into the ice-covered ocean). Drawbacks in wave modelling undermine our understanding and ability to protect this delicate ocean and coastal environment.
-
The AA4528 corridor dataset contains the Matlab scripts for the corridor algorithm, ice shelf locations and file extensions. The corridor algorithm is designed to calculate the parts of the ocean which can directly propagate swell into an exposed ice shelf. The algorithm achieves this as an expansion of the coastal exposure algorithm (Reid and Massom, 2021), with the details of the inner working of the algorithm work presented in the paper attached with this dataset. Corridors can be used to calculate the frequency of swell reaching an ice shelf per year and can be combined with hindcasts to extract relevant wave data to an ice shelf for modelling or data analysis purposes. The corridor algorithm requires sea ice concentration data, which was provided by the NSIDC Sea ice concentrations from the Nimbus-7 SMMR and DMSP SSM/I-SSMIS Passive Microwave Data, Version 1 (https://nsidc.org/data/nsidc-0051). Ice shelf coordinates were extracted from the gfsc_25s.msk that come with the sea ice data, with the aid of Antarctic Mapping Toolbox (Greene et al., 2017), and were attached separately to make editing more consistent. As this is designed to use daily sea ice data from the 1st of January 1979 onwards, I’ve also attached the sea ice files for the off-days when the sea-ice data was taken every 2nd day. Th file extensions script was also included to be able to switch through off-day files and changes that occur with the NSIDC file format. The ocean hindcast that the corridor algorithm was built around is the CAWCR Wave Hindcast – Aggregated Collection (https://data.csiro.au/collections/collection/CI39819v005). The corridor algorithm uses daily data to make it consistent with the sea ice data and calculated the maximum significant wave height for each cell present in the hindcast. Data that was extracted from it was the maximum daily significant wave height recorded in the corridor and the direction of that cell. Data was taken from 01/09/1979 to 31/08/2019 giving 40 years of data which accounts for seasonality of corridors. The excel spreadsheet attached contains relevant corridor data for each ice shelf with an area greater than 500 km^2. Area was determined by either the supplementary files from Rignot et. al., 2013, or ice shelf areas from the Antarctic mapping toolbox (Greene et al., 2017). Angle1 and Angle2 were the ones used in the direction filter, and there should be a comment in the filter with how it handles if Angle 1 is greater than Angle 2 or vice versa. Ac is the corridor area, PA is potential corridor area (i.e. the absolute max it could be with the settings we used, Ac_max is the maximum corridor area, D_cor is the days that corridors were present, Hs is significant wave height and LW (large waves) is counting days per year when significant wave heights greater than or equal to 6 m (Morim et al., 2021). Refs: Greene, C. A., Gwyther, D. E. and Blankenship, D. D. (2017) ‘Antarctic Mapping Tools for MATLAB’, Computers and Geosciences, 104, pp. 151–157. doi: 10.1016/j.cageo.2016.08.003. Morim, J. et al. (2021) ‘Global-scale changes to extreme ocean wave events due to anthropogenic warming’, Environmental Research Letters, 16(7), p. 074056. doi: 10.1088/1748-9326/ac1013. Reid, P. and Massom, R. (2021) ‘Change and Variability in Antarctic Coastal Exposure , 1979-2020’. In pre-print (https://assets.researchsquare.com/files/rs-636839/v1/02002d0b-2c6c-402b-8e14-7f77075d8f90.pdf?c=1631885736) Rignot, E. et al. (2013) ‘Ice-shelf melting around antarctica’, Science, 341(6143), pp. 266–270. doi: 10.1126/science.1235798.
-
This dataset contains the Voyage Data from voyage 202122050 undertaken by the RSV Nuyina between February 12th and March 27th 2022. The principal objectives of the voyage were to retrieve equipment and exchange personnel from Davis Station, and resupply Macquarie Island Station. The EK80 acoustic instruments, underway oceanographic instruments in the OceanPack system, the ice and wave radar, and meteorological instruments were all run during this voyage. Whole of voyage data from the RSV Nuyina underway instruments. Includes uncontaminated seawater, meteorological, and wave radar data interpolated to 1 minute measurements. Wherever possible, each parameter and its associated unit of measurement complies with the NetCDF Climate and Forecast (CF) Metadata Convention Standard Name Table (Version 29) - “voyage_202122050\underway_merger\netcdf\202122050_1min_all.nc