Waves and Currents

It is estimated that 75% of waves across the World Ocean are generated by distant storms which propagate as swell. The strongly swell- dominated areas known as a swell pools, act as a response and/or impact factor for climate change. Nowadays, a unique swell spectra dataset on a continuous and global basis is available for the scientific community from Advanced Synthetic Aperture Radar (ASAR) aboard Envisat satellite operating in wave mode for 10 years. In this paper, a method of a dynamical validation approach for SAR swell spectra is developed, in which the in situ buoy spectra are reconstructed, partitioned, and retro-propagated to the vicinity of satellite observation along the great circle based upon the linear wave theory. More than 40,000 ASAR-buoy swell partitions are dynamically collocated for the full mission of Envisat, making this study the first to provide detailed quality assessment for ASAR derived ocean swell spectra. Comparison results show a general statistics of 0.40 m, 44.99 m and 16.89 ̊ for swell height, peak wavelength and direction RMSE, indicating a good agreement with buoy in-situ in Pacific Ocean. Furthermore, a typical case is presented and discussed, describing the swell generated in Southern Ocean propagating to North Pacific, captured by ASAR in the middle of Pacific and finally observed by NDBC buoy off the California coast.

Sea surface winds, waves and currents are the three most important, as well as basic ocean dynamic parameters in the air-sea interface. While derivation or retrieval of the former two parameters from spaceborne SAR data is in a mature stage and even becomes operational now, derivation of sea surface currents still remains some limitation and difficulties. The Along-Track-Interferometry (ATI) is considered to be the most effective configuration to derive sea surface current field with a spatial resolution in scale of kilometer from spaceborne SAR data. The launching of TanDEM-X by the German Aerospace Center (DLR) in 2007 makes it possible to derive sea surface currents field from spaceborne ATI in high spatial resolution.

The AOI is in the Hangzhou Bay, East China Sea, where the tial current can reach 3 m/s maximum. On the other hand, the tidal current has strong interaction with the piles of offshore wind turbins in the bay [Li et al., 2014]. Following this previus finding, we conduct an in situ compaign in July, 2015 and the Tandem-X ATI data were acquired during the campaign. The derived sea surface current field using the ATI data is compared with in situ measurements, as well as the FVCOM simulation.

On the other hand, we also tried to derive sea surface current field in the Hangzhou bay using the TanDEM-X pursuit monostatic mode data. Two independent TerraSAR-X and TanDEM-X Stripmap data were acquired on Dec.3, 2014 over the bay, but with only ten seconds interval. The often used Maximum Cross-Correlation method for deriving sea surface current field from optical remote sensing data is adapted to the TanDEM-X pursuit monostatic mode data to derive tidal current. Although the in situ measurement was not available during the TanDEM-X acquisation, the simulated tidal current field using FVCOM shows very good agreement with SAR retrieval.  

Reference:

Li et al. (2014), SAR observation and numerical modeling of tidal current wakes at the East China Sea offshore wind farm, JGR-Oceans, 119, doi:10.1002/2014JC009822.

Mode-2 internal waves are usually not as energetic as larger mode-1 Internal Solitary Waves (ISWs), but they have attracted a great deal of attention in recent years because they have been identified as playing a significant role in mixing shelf waters (e.g. Gregg and Klymak, 2014). This mixing is particularly effective for mode-2 ISWs because the location of these waves in the middle of the pycnocline plays an important role in eroding the barrier between the base of the surface mixed layer and the stratified deep layer below. An urgent problem in physical oceanography is therefore to account for the magnitude and distribution of ISW-driven mixing, including mode-2 ISWs. Several generation mechanisms of mode-2 ISWs have been identified. These include: (1) mode-1 ISWs propagating onshore (shoaling) and entering the breaking instability stage, or propagating over a steep sill; (2) a mode-1 ISW propagating offshore (antishoaling) over steep slopes of the shelf break, and undergoing modal transformation; (3) intrusion of the whole head of a gravity current into a three-layer fluid; (4) impingement of an internal tidal beam on the pycnocline, itself emanating from critical bathymetry; (5) nonlinear disintegration of internal tide modes; (6) lee wave mechanism. In this paper we provide methods to identify internal wave features denominated “Wave Tails” in SAR images of the ocean surface, which are many times associated with second mode internal waves. The SAR case studies that are presented portray evidence of the aforementioned generation mechanisms, and we further discuss possible methods to discriminate between the various types of mode-2 ISWs in SAR images, that emerge from these physical mechanisms. Some of the SAR images correspond to numerical simulations with the MITgcm in fully nonlinear and nonhydrostatic mode and in a 2D configuration with realistic stratification, bathymetry and other environmental conditions. Results of a global survey with some of these observations is presented, including: the Mascarene Ridge of the Indian Ocean; South China Sea; Andaman Sea; tropical Atlantic off the Amazon shelf break, Bay of Biscay of the western European margin; etc. The survey included the following SAR missions: ERS-1/2; Envisat; TerraSAR-X; Kompsat-5; Sentinel-1.

In oceanography, one of the important products that can be provided from satellites is the directional spectrum of ocean waves (also called 2D spectrum), which describes the energy of the surface ocean waves as a function of wave number and direction of propagation. This information is essential for wave forecast systems, improvement of wave models, wave climate studies and scientific studies related to the ocean/atmosphere interface, coastal and marginal ice zone processes. This has motivated the specification of SAR instruments to deliver 2D wave spectra (ERS, ENVISAT, SENTINEL-1, RADARSAT, etc.), and the future CFOSAT mission [1] which will embark the wave scatterometer SWIM (low incidence real aperture scanning scatterometer) to provide directional wave spectra with wavelengths from 70 to 600 m.

Because directional spectra contain a large amount of information, a way to use this information is usually to decompose the two-dimensional spectra into several partitions, each of them characterizing a “wave component”. For example partitioning wave spectra is a way to distinguish swell components from wind sea components that have different spectral characteristics and correspond to different wave evolutions (swell waves, in opposite to wind sea waves, re defined as ocean waves which are no longer under the influence of the local wind). Partitioning is a key issue for a good retrieval of wave parameters such as significant wave height, peak direction and wavelength, of the different wave components in a 2D wave spectrum.

Partitioning methods of wave spectra have originally been developed for analysing outputs of wave forecasting numerical models. The most famous method is the watershed method proposed by Hanson and Phillips [2]. Extending the application of this method to satellite data raises several difficulties because of the presence of noise in the data, which makes the result of the partitioning rather sensitive to the noise.

Our presentation will address this issue in the context of 2D wave spectra observed from i) SAR (Sentinel-1), ii) simulated wave spectra expected from SWIM observations (including noise effects) and iii) observed wave spectra from the airborne wave scatterometer KuROS [3]. We will compare different adaptations of the watershed principle to account for noise effects. Furthermore, we will present results obtained from an alternative method, namely a method based on a Bayesian approach. In opposite to the watershed method, the bayesian method presents the advantage of taking explicitly into account noise into the partitioning process and can even be used to estimate the noise floor. After explaining both methods and showing comparative results, we will discuss the pros, cons and limits of both partitioning techniques.

References:

[1] Tison C., T. Amiot, J. Bourbier, D. Hauser, V. Enjolras, L. Rey, P. Castillan, Directional wave spectrum estimation by SWIM instrument on CFOSAT, Proceedings of the IGARSS conference, Cape Town (South Africa), July 2009

[2] Hanson J.L. and O.M. Phillips, J. Atmos. And Oceanic Tech., vol18, 2001, p 277-293

[3]Caudal G., D. Hauser, R. Valentin, C. Le Gac, KUROS : A new airborne  Ku-band Doppler radar observation of  surfaces,  Jour. Atmos. and Oceanic Technology, Vol. 31, No. 10. , 2223-2245, 2014

Sentinel-1 A now routinely acquires data over the ocean. ESA processes Sentinel-1 data through the Payload Data Grounnd Segment up to Level-2 for Copernicus users. Level-2 consists of geo-located geophysical products for wind, wave and ocean current applications, referred to as the Level-2 Ocean (OCN) products.
This paper focuses on ocean waves as measured in Wave Mode and Strip Map Mode. A validation of these measurements has been carried out.

Sentinel-1A wave measurements provide 2-D ocean swell spectra (2-D wave energy distribution, function of wavelength and direction) as well as classical integrated parameters such as significant wave height, dominant wavelength and direction. As Sentinel-1 A is the only operational sensor able to make this type of ocean swell spectrum measurements, several dedicated
methodologies have been set up for validation.

In addition, the possibilities of deriving new parameters such as wave groups or wind sea characteristics thanks to the new capacities of the sensor such as the 20 kmx20km coverage for the Wave Mode or its higher resolution will be discussed.
Examples of use of these data to study waves generated from hurricanes and diffraction effects in shallow waters will be shown.