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.

Time series of metocean variables derived form WAMOS (marine radar) data collected during the Antarctic Circumnavigation Expedition (ACE, https://spi-ace-expedition.ch/), from December 2016 to March 2017. 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. 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. By installing a Wave and Surface Current Monitoring System (WaMoS II, a marine X-Band radar) on the research vessel Akademic Thresnikov and using the meteo-station and GPS on-board, this project has produced a large database of winds, waves and surface currents. Data were collected during the Antarctic Circumnavigation Expedition, which took place from Dec. 2016 to Mar. 2017. The dataset contains timeseries of relevant metocean variables divided in - Sea state and current parameters (PARA, MPAR) - Sea state and current parameters (PEAK, MPEK) - Ship course, position and speed (COURSE) - Wind speed and direction file (WIND) ********************************************************** Sea state and current parameters files (PARA, MPAR) File Name: -Prefix-_-rigID-_YYYYMM.txt - Prefix: 1) ‘PARA’ : spatial mean of the parameters (that pass the WaMoS II internal quality control) averaged over WaMoS II analysis areas (up to 9) placed within the radar field of view. 2) ‘MPAR’ : temporal average parameters calculated using all data collected during the past dt=20 minutes of the time specified in the file. - YYYY : Year. - MM : Month. - rigID : WaMoS II platform’s ID code (3 letters) Time reference: CPU clock. Values of missing parameters are set to -9, -9.0. List of parameters: - date : Date and TIME of acquisition (YYYYMMDDHHMMSS). - Hs : Significant wave height (m). - Tp : Peak wave period (s). - Tm2 : Mean wave period (s). - Lp : Peak wave length (m). - MDir : Mean wave direction (deg). - PDir : Peak wave direction (deg). - TpS : First swell system - wave period (s). - PDS : First swell system - peak wave direction (deg). - lpS : First swell system - peak wave length (m). - TpW : Wind sea peak wave period (s). - PDW : Wind sea wave direction (deg). - lpW : Wind sea wave length (m). - Usp : Surface current speed (m/s). - Udir : Surface current direction (deg). - IQ : Quality index, ranging from 0 ('no problems detected') to 999 ('images cannot be analysed'). - NSPEC : Number of averaged spectra. - INDEX : Quality index threshold (OK: IQ<Index). - Hmax : Maximum wave height (m). - Tlim : Limit period to separate Swell/Wind Sea (s). - ELEVL : Error number. - CFG-Date : Date/time of last wamos.cfg change (DD-MM-YYYY HH.MI.SS). ********************************************************** Sea state and current parameters files (PEAK, MPEK): File Name: -Prefix-_-rigID-_YYYYMM.txt - Prefix: 1) ‘PEAK’ : spatial mean of the parameters (that pass the WaMoS II internal quality control) averaged over WaMoS II analysis areas (up to 9) placed within the radar field of view. 2) ‘MPEK’ : temporal average parameters calculated using all data collected during the past dt=20 minutes of the time specified in the file. - YYYY : Year. - MM : Month. - rigID : WaMoS II platform’s ID code (3 letters) Time reference: CPU clock. Values of missing parameters are set to -9, -9.0. List of parameters: - date : Date and TIME of acquisition (YYYYMMDDHHMMSS). - Hs : Significant wave height (m). - Tp : Peak wave period (s). - PDir : Peak wave direction (deg). - Lp : Peak wave length (m). - HsW : Wind sea significant wave height (m). - TpW : Wind sea wave period (s). - PDW : Wind sea wave direction deg). - lpW : Wind sea wave length (m). - HSS1 : First swell system significant wave height (m). - Tps1 : First swell system: wave period (s). - PDs1 : First swell peak wave direction (deg). - lps1 : First swell peak wave length (m). - HSS2 : Second swell system significant wave height (m). - Tps2 : Second swell system: wave period (s). - PDs2 : Second swell peak wave direction (deg). - lps2 : Second swell peak wave length (m). - HSS3 : Third swell system significant wave height (m). - Tps3 : Third swell system: wave period (s). - PDs3 : Third swell peak wave direction (deg). - lps3 : Third swell peak wave length (m). - Us : Surface current speed (m/s). - Ud : Surface current direction (deg). - IQ : Quality index. - Tlim : Limit period to separate Swell/Wind Sea (s). - SPR : Mean wave spreading. - CSI : Cross sea index. - GAM : Enhancement factor of the jonswap spectrum. - NORI : from compass or GPS (0 = enable 1 = disable). - ELEVL : Error number - CFG-Date : Date/time of last wamos.cfg change (DD-MM-YYYYHH.MI.SS). ********************************************************** Ship course, position and speed file (COURSE): File Name: -Prefix-_-rigID-_YYYYMM.txt - Prefix: ‘COURSE’ : Input from NMEA systems. - YYYY : Year. - MM : Month. - rigID : WaMoS II platform’s ID code (3 letters) Time reference: CPU clock. Values of missing parameters are set to -9, -9.0. List of parameters: - date : Date and TIME of acquisition (YYYYMMDDHHMMSS). - LAT : Latitude (deg). - LONG : Longitude (deg). - GYROC : Ship gyro compass (deg). - GPS : GPS course (deg). - Shipsp : Ship speed (kn). - Depth : Water depth (m). - GPS-Speed : GPS-Speed (kn). - ASDPW : Internal parameter. ********************************************************** Wind speed and direction file (WIND): File Name: -Prefix-_-rigID-_YYYYMM.txt - Prefix: ‘WIND’ : Input from NMEA systems. - YYYY : Year. - MM : Month. - rigID : WaMoS II platform’s ID code (3 letters) Time reference: CPU clock. Values of missing parameters are set to -9, -9.0. List of parameters: - date : Date and TIME of acquisition (YYYYMMDDHHMMSS). - LAT : Latitude (deg). - LONG : Longitude (deg). - WIND SPEED : Wind speed (m/s). - DIR : Wind direction (coming from) (deg). - WIND SPEED10 : Wind speed at 10 meters height (m/s). - TRUE DIR : Wind direction relative to north (deg).

Raw GPS and ship motion data collected during the Antarctic Circumnavigation Expedition 2016/2017. 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. By installing a Wave and Surface Current Monitoring System (WaMoS II, a marine X-Band radar) on the research vessel Akademic Thresnikov and using the meteo-station and GPS on-board, this project has produced a large database of winds, waves and surface currents. Dara were collected during the Antarctic Circmumnavigaion Expedition, which took place from Dec. 2016 to Mar. 2017. The instrumentation operated in any weather and visibility conditions, and at night, monitoring the ocean continuously over the entire Circumnavigation. Records can support 1. the assessment of metocean conditions in the Southern Oceans; and 2. calibration and validation of wave and global circulation models. Data - AAS_4434_ACE_GPS contains basic metereological conditions acquired form the ship’s meteo-station, gepgraphical coordinates (latitude, longitude and altitude) from the ship’s GPS and ship motion data from the ship’s Inertial Measurement Unit (IMU). These data are stored as time series with a sampling frequency of 1Hz.

This dataset contains acoustic recordings from Directional Frequency Analysis and Recording (DIFAR) sonobuoys that were deployed from 22 January – 18 March 2017 during the Antarctic Circumnavigation Expedition. During the 52 days at sea 301 sonobuoys were deployed yielding 492 hours of acoustic recordings. Two models of sonobuoys were used during the voyage: 1 was a bespoke reusable DIFAR buoy based on a sensor and radio from an AN/SSQ-53F sonobuoy (Ultra Electronics: SonobuoyTechSystems, USA) and 300 were re-lifed AN/SSQ-955-HIDAR (deployed in DIFAR compatibility mode; Ultra Electronics Sonar Systems, UK). Two dedicated acousticians monitored round-the-clock for blue, fin, sperm, humpback, minke, killer, and sei whales, and crabeater, leopard, Ross, and weddell seals and in all weather conditions. During ACE, we conducted a broad-scale, passing-mode passive acoustic survey for marine mammals in the Southern Ocean. Listening stations were conducted by deploying SSQ955 HIDAR sonobuoys in DIFAR (standard) mode to monitor for and measure bearings to vocalising whales while the ship was underway (Gedamke and Robinson 2010, Miller et al. 2015). During transit, listening stations were conducted every 30-60 nmi in water depths greater than 200 m. Sonobuoys were occasionally deployed with spacing less than 30 nmi in an attempt to more precisely determine spatial extent and vocal characteristics of calls that were believed to be coming from animals relatively close to the ship’s track. During terrestrial stopovers and marine science stations, sonobuoys were deployed approximately 2-4 nmi prior to stopping in order to attempt to monitor them for the full six-hour duration of their operational life. This distance ensured good radio signal while minimising acoustic interference from the vessel. The sampling regime was chosen to balance spatial resolution with the finite number of sonobuoys available for this study. Instrumentation, software, and data collection At each listening station, a HIDAR sonobuoy was deployed with the hydrophone set to a depth of 140 m. Sonobuoys transmitted underwater acoustic signals from the hydrophone and directional sensors back to the ship via a VHF radio transmitter. Radio signals from the sonobuoy were received using an omnidirectional VHF antenna (PCTel Inc. MFB1443; 3 dB gain tuned to 144 MHz centre frequency) and a Yagi antenna (Broadband Propagation Pty Ltd, Sydney Australia) mounted on the top of the helicopter control room at a height of 23.0 m. The antennas were each directly connected to a WiNRADiO G39WSBe sonobuoy receiver via low-loss LMR400 coaxial cable. The radio reception range on the Yagi antenna was similar to previous Antarctic voyages, and was adequate for monitoring and localisation typically out to a range of 12-14 nmi, provided that the direction to the sonobuoy was close (i.e. within around 30o) to the main axis of the antenna. The radio reception on the omnidirectional antenna typically provided 5-8 nmi of omnidirectional reception from sonobuoys. At transit speed (14-15 knots), the Yagi antenna provided about 55 minutes of acoustic recording time per sonobuoy Using both antennas together were able obtain radio reception for up to six hours (i.e. the maximum life of a 955 sonobuoy) when sonobuoys were deployed within 5 nmi of a marine science station. Received signals were digitised via the instrument inputs of a Fireface UFX sound board (RME Fireface; RME Inc.). Digitised signals were recorded on a personal computer as 48 kHz 24-bit WAV audio files using the software program PAMGuard (Gillespie et al. 2008). Data from both the Yagi and Omnidirectional antenna were recorded simultaneously as WAV audio channels 0 (left) and 1 (right). Each recorded WAV file therefore contains a substantial amount of duplication since both antennas and receivers were usually receiving the same signals from the same sonobuoy. Directional calibration The magnetic compass in each sonobuoy was calibrated/validated upon deployment as described by Miller et al. (2015, 2016). Calibration procedure involved measuring the mean bearing error and standard deviation of errors between the GPS-derived bearing from the sonobuoy to the ship and the magnetic bearing to the ship noise detected by the sonobuoy. 15-20 bearings were used for each calibration as the ship steamed directly away from the deployment location. Intensity calibration Obtaining calibrated intensity measurements from sonobuoys not only requires knowledge of the sensitivity of the hydrophone, but also the calibration parameters of the radio transmitter and radio receiver. Throughout the voyage, a hydrophone sensitivity of -122 dB re 1 V/micro Pa was applied to recordings via the Hydrophone Array Manager in PAMGuard. This value is defined in the DIFAR specification as the reference intensity at 100 Hz that will generate a frequency deviation of 25 kHz (Maranda 2001), thus the specification combines the hydrophone sensitivity and transmitter calibration. In line with manufacturers specifications, the WiNRADiO G39 WSB had a measured voltage response of 1 V-peak–peak (approximately -3 dB) at 25 kHz frequency deviation (Miller et al. 2014), and this was subtracted from the hydrophone sensitivity to yield an total combined factor of 125 dB re 1 V/µPa. The gain of the instrument input on the Fireface UFX was set to 20 dB, yielding a maximum voltage input voltage range of 8.36 V peak–peak. These calibration settings, along with the shaped filter response provided by Greene et al. (2004) make it possible to obtain calibrated pressure amplitude from the recorded WAV audio files. Sonobuoy deployment metadata The PAMGuard DIFAR Module (Miller et al. 2016) was used to record the sonobuoy deployment metadata such as location, sonobuoy deployment number, and audio channel in the HydrophoneStreamers table of the PAMGuard database (PamguardBlueWhale-2015-02-03.mdb). A written sonobuoy deployment log (Sonobuoy deployment logbook - 2015 Tangaroa.pdf) was also kept during the voyage, and this includes additional notes and additional information not included in the PAMGuard Database such as sonobuoy type, and sonobuoy end-time. Real-time monitoring and analysis (Acoustic event log) Aural and visual monitoring of audio and spectrograms from each sonobuoy was conducted using PAMGuard for at least an hour at each listening station. Two different spectrograms were typically viewed, one for low-frequency sounds with the following parameters: 250 Hz sample rate; 256 sample FFT; 32 sample advance between time slices. The other spectrogram was used to view mid-frequency sounds with the following parameters: 8000 Hz sample rate; 1024 sample FFT; 128 sample advance between time slices. Monitoring was conducted in real-time as data were being acquired, and the intensity scale of the spectrogram was adjusted by the operator to suit the ambient noise conditions. When detections from marine mammals, ice, and other sources were detected, they were classified manually, and their time and frequency bounds marked on the spectrogram. The PAMGuard DIFAR module (Miller, Calderan, et al. 2016) was then used to measure the direction of arrival and intensity of suitable calls such as tonal, frequency-modulated, and pulsed calls of baleen whales, whistles and trills from pinniped, and some whistles from toothed whales. Echolocation clicks from sperm whales (Physeter macrocephalus) were noted in the PAMGuard UserInput (free form notes stored in the PAMGuard Sqlite database), but could not be localised with the DIFAR module due to limitations inherent in directional sensors in the sonobuoy. Detection, bearing, and intensity measurements were saved both within a PAMGuard binary file and within the DIFAR_Localisation table of the PAMGuard database. In addition to PAMGuard binary files and audio files, the PAMGuard settings and metadata were saved to the PAMGuard Sqlite database. During Leg 3, some experimental trials were conducted with sonobuoys deployed in pairs with one hydrophone set to a depth of 140m and the other set to either 300m or 30m (the other two depth options available in the sonobuoy settings). The aim of these experiments was to investigate any differences with received level and the depth of the receiver. Recordings collected over a range of received levels as the vessel headed away from vocalising whales can also allow estimates of bearing accuracy for weak calls (by comparing bearings to the same call from different buoys) and the relative detection probability for calls under different noise conditions (by using the signals from each buoy in a similar way to independent observer experiments). References Greene, C.R.J. et al., 2004. Directional frequency and recording ( DIFAR ) sensors in seafloor recorders to locate calling bowhead whales during their fall migration. Journal of the Acoustical Society of America, 116(2), pp.799–813. Maranda, B.H., 2001. Calibration Factors for DIFAR Processing, Miller, B.S. et al., 2014. Accuracy and precision of DIFAR localisation systems: Calibrations and comparative measurements from three SORP voyages. Submitted to the Scientific Committee 65b of the International Whaling Commission, Bled, Slovenia. SC/65b/SH08, p.14. Miller, B.S. et al., 2016. Software for real-time localization of baleen whale calls using directional sonobuoys: A case study on Antarctic blue whales. The Journal of the Acoustical Society of America, 139(3), p.EL83-EL89. Available at: http://scitation.aip.org/content/asa/journal/jasa/139/3/10.1121/1.4943627. Miller, B.S. et al., 2015. Validating the reliability of passive acoustic localisation: a novel method for encountering rare and remote Antarctic blue whales. Endangered Species Research, 26(3), pp.257–269. Available at: http://www.int-res.com/abstracts/esr/v26/n3/p257-269/.

WAMOS (marine radar) data collected during the Antarctic Circumnavigation Expedition (ACE, https://spi-ace-expedition.ch/), from December 2016 to March 2017. 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. By installing a Wave and Surface Current Monitoring System (WaMoS II, a marine X-Band radar) on the research vessel Akademic Thresnikov and using the meteo-station and GPS on-board, this project has produced a large database of winds, waves and surface currents. Dara were collected during the Antarctic Circmumnavigaion Expedition, which took place from Dec. 2016 to Mar. 2017. The instrumentation operated in any weather and visibility conditions, and at night, monitoring the ocean continuously over the entire Circumnavigation. Records can support 1. the assessment of metocean conditions in the Southern Oceans; and 2. calibration and validation of wave and global circulation models. Data - AAS_4434_ACE_WAMOS contains sea state conditions monitored continuously with a Wave and Surface Current Monitoring System (WaMoS II), a wave devise based on the marine X-Band radar (see Hessner, K. G., Nieto-Borge, J. C., and Bell, P. S., 2007, Nautical Radar Measurements in Europe: Applications of WaMoS II as a Sensor for Sea State, Current and Bathymetry. In V. Barale, and M. Gade, Sensing of the European Seas, pp. 435-446, Springer). Sea state consists of the directional wave energy spectrum, angular frequency and direction of propagation. Basic parameters such as the significant wave height (a representative measure of the average wave height), the dominant period, wavelength, mean wave direction, etc… were inferred from the wave spectrum. Surface current speed and the concurrent direction were also detected. Post processed data are available anytime the X-Band radar was operated in a range of 1.5NM; a full spectrum was generally obtained evert 20 minutes. Data are subdivided in: - WaMoS II frequency spectrum (1-D spectra) - WaMoS II wave number spectrum (2-D spectra) - WaMoS II frequency direction spectrum (2-D spectra) Data are quality controlled. ************************************************************************************************************** File informations Path to the spectra: \RESULTS\YYYY\MM\DD\HH\ : Year, month, day, hour. space\ : spatial mean results. single\ : raw spectra. mean\ : time averaged files. Header of the spectra: Additional information that might be needed for data analysis is stored in the headers. The output results generated using different WaMoS II software modules are separated by comment lines starting with ‘CC’. All headers are subdivided into: 1) Polar Header: including data acquisition parameters. 2) Car Header: including Cartesian transformation parameters. 3) Wave-Current Analysis Header: including wave and current analysis related parameters. There is a keyword of maximum 5 characters in each line of the header followed by some values and a comment, after the comment marker ‘CC’, describing the keyword. Values of missing parameters are set to -9, -9.0, -99.0, etc. depending on the data type. The 'end of header' keyword 'EOH', indicated the last line of the header section. ******************************************************************* WaMoS II frequency spectrum (1-D spectra): File Name: YYYY : Year. MM : Month. DD : Day. HH : Hour. MM : Minute. SS : Second. rigID : WaMoS II platform’s ID code (3 letters) Suffix: ’*.D1S’ : spatial mean of the spectra (that pass the WaMoS II internal quality control) averaged over WaMoS II analysis areas (up to 9) placed within the radar field of view. ‘*.D1M’ : temporal average spectra calculated using all spectra collected during the past dt=30 minutes of the time specified in the file. Time reference: CPU clock. Data Content: Frequency (f - Hz). Spectral energy (S(f) - m*m/Hz). Mean Wave Direction (MDIR(f) - deg), ���coming from’. Directional Spreading (SPR(f) - deg/Hz). ******************************************************************* WaMoS II wave number spectrum (2-D spectra): File Name: YYYY : Year. MM : Month. DD : Day. HH : Hour. MM : Minute. SS : Second. rigID : WaMoS II platform’s ID code (3 letters) Suffix: ’*.D2S’ : spatial mean of the spectra (that pass the WaMoS II internal quality control) averaged over WaMoS II analysis areas (up to 9) placed within the radar field of view. ‘*.D2M’ : temporal average spectra calculated using all spectra collected during the past dt=30 minutes of the time specified in the file. Time reference: CPU clock. Data Content: Spectral energy (S(kx,ky) - m*m/(Hz*rad)) as a function of wave number (kx and ky - rad/m). Data related header information MATRIX: Size of Matrix. DKX: Spectral resolution in Kx direction (2*Pi/m). DKY: Spectral resolution in Ky direction (2*Pi/m). ******************************************************************* WaMoS II frequency direction spectrum (2-D spectra): File Name: YYYY : Year. MM : Month. DD : Day. HH : Hour. MM : Minute. SS : Second. rigID : WaMoS II platform’s ID code (3 letters) Suffix: ‘*.FTH’ : spatial mean of the spectra (that pass the WaMoS II internal quality control) averaged over WaMoS II analysis areas (up to 9) placed within the radar field of view. ’*.FTM’ : temporal average spectra calculated using all spectra collected during the past dt=30 minutes of the time specified in the file. Time reference: CPU clock. Data Content: Spectral energy (S(f,θ) - m*m/(Hz*rad)) as a function of frequency (f – Hz) and direction (θ - deg). Data information Mf : number of frequency sampling points. Mth : number of direction sampling points. Data Matrix: Row 1 frequency sampling points, Column 1 direction sampling points. The dataset download also includes a file, "Available_Measurements", which is a general calendar that provides the list (day and time) of available measurements.