Multiple satellite observations of oceanic planetary waves: techniques and findings

Recent satellite-based observations of oceanic planetary waves have improved our knowledge of the wave properties and lead to advancements in the theory. Firstly, we review some of the techniques adopted to extract the information on planetary wave properties, illustrating them with examples based on satellite altimeter data, and we summarize the main findings. Then we discuss a cross-spectral approach for the comparison of the wave signals in the different datasets (altimetry, ocean colour and sea surface temperature) that is necessary to unveil the causes of the newly found wave signature in satellite-derived maps of phytoplankton chlorophyll, a discovery that is attracting considerable interest as it implies some effects of the waves on biology

SOFT feature-tracking software handbook

This handbook (SOFT_WP31_handbook.pdf) describes the suite of MATLAB programs developed within Work Package 3, task 3.1 of the SOFT Project, for the tracking of large-scale, westward propagating features (planetary waves or westward-travelling eddies) in altimeter data and the removal of the identified features from the datasets. The suite has been applied to TOPEX/POSEIDON data over the Azores region (one of the SOFT study regions) but its modularity makes it adaptable in a straightforward way to other datasets and other regions. The companion to this handbook is the progress report on task 3.1 released in January 2003 (SOFT_WP31_report.pdf), which presents the rationale to the study and gives ample details on the scheme adopted for the fitting of elementary waves (according to a Gaussian wave shape model) to altimeter data. A synopsis of the fitting scheme is briefly recalled in the following sections of this document, for the benefit of the reader. All the code listings are in the appendix. The forecasting of the westward-propagating fields (which is the object of task 3.2 in Work Package 3 id described in version 1 of another report, SOFT_WP32_rep1.pdf

SOFT Wave forecasting report - v.1.0

This report (SOFT_WP32_rep1.pdf) describes the first version of the wave forecasting code developed within Work Package 3, task 3.2 (implementation of a hybrid SOFT tracking system) of the SOFT Project. The forecasting of westward propagating signals (planetary waves or westward-travelling eddies), using the fields of tracked wave from Work Package 3, task 3.1, is one of the two components of the hybrid system which is the overall deliverable of task 3.2. The results presented here are provisional and are likely to be replaced as research proceeds. Related to this report are two other documents:- the progress report on task 3.1 released in January 2003(SOFT_WP31_report.pdf), which presents the rationale to the study and gives ample details on the scheme adopted for the fitting of elementary waves (according to a Gaussian wave shape model) to altimeter data (see also the paper by Cipollini, 2003);- the handbook SOFT_WP31_handbook.pdf describing the suite of MATLAB programs developed within Work Package 3, task 3.1 of the SOFTProject, for the tracking of large-scale, westward propagating features (planetary waves or westward-travelling eddies) in altimeter data and the removal of the identified features from the datasets. The suite has been applied to TOPEX/POSEIDON data over the Azores region (one of the SOFTstudy regions) and the output results have been used for the forecast

SOFT Development of feature tracking methods

The present report describes the work carried out within task 3.1 of Work Package 3 of the SOFT Project. The above task is ‘Development of feature tracking methods’ and consists of the development of a software to track large-scale, westward propagating features (planetary waves or westward-travelling eddies) in the altimetric datasets, and in the removal of the identified features from the datasets. The residual field (that is the original dataset minus the tracked features) is then made available to the other work packages in the Project

Using remotely sensed data to modify wind forcing in operational storm surge forecasting

Storm surges are abnormal coastal sea level events caused by meteorological conditions such as tropical cyclones. They have the potential to cause widespread loss of life and financial damage and have done so on many occasions in the past. Accurate and timely forecasts are necessary to help mitigate the risks posed by these events. Operational forecasting models use discretisations of the governing equations for fluid flow to model the sea surface, which is then forced by surface stresses derived from a model wind and pressure fields. The wind fields are typically idealised and generated parametrically. In this study, wind field datasets derived from remotely sensed data are used to modify the model parametric wind forcing and investigate potential improvement to operational forecasting. We examine two methods for using analysis wind fields derived from remotely sensed observations of three hurricanes. Our first method simply replaces the parametric wind fields with its corresponding analysis wind field for a period of time. Our second method does this also but takes it further by attempting to use some of the information present in the analysis wind field to estimate future wind fields. We find that our methods do yield some forecast improvement, most notably for our second method where we get improvements of up to 0.29 m on average. Importantly, the spatial structure of the surge is changed in some places such that locations that were previously forecast small surges had their water levels increased. These results were validated by tide gauge data

EUMETSAT Invitation To Tender 14/209556: JASON-CS SAR Mode Sea State Bias Study. Final report

This document represents the final report of a study funded by EUMETSAT about SAR mode Sea State Bias (SSB) for the Sentinel-6/Jason-CS mission. The study comprises a critical review of SSB estimation methods in conventional (low-resolution mode or LRM) altimetry, theoretical considerations about the effect of swell on SAR altimeter waveforms and empirical investigations with Cryosat-2 SAR mode data to detect swell effects in L1B and Level 2 Sea Surface Height (SSH). The report concludes by summarising the basis for the selection and derivation of the SAR altimeter sea state bias correction algorithm and the methods available to calibrate and validate SAR mode SSB corrections. Theoretical considerations based on simple SAR waveform modelling indicate that multipeaked waveforms could occur in the presence of swell, but that effects become clearly detectable only when swell height exceeds 4 meters, which is relatively rare. In the case of the Cryosat-2 data examined in this study, only 2% of samples satisfied this condition. Experimental investigations of Cryosat-2 SAR mode data in different swell conditions produce no consolidated evidence of swell effects. Although anomalous 20Hz waveforms are occasionally observed, no statistically detectable effect of swell is obtained in the overall results for average L1B waveform shapes and L2 1Hz SSH biases and precisions. However, it is stressed that analyses in this study were limited geographically by the availability of Cryosat-2 SAR mode acquisitions over the ocean that could be collocated with Envisat ASAR swell data. It is strongly advised that analyses should be repeated with a broader geographical scope, including data from the central Pacific and the Southern Ocean where high sea state and swell conditions are more prevalent. It is suggested that this could be achieved using Sentinel-3 SRTM and Sentinel-1 L2 swell products, should such data be available. Empirical SSB estimation methods offer the only viable way forward at present to estimate SAR mode SSB. Parametric, non-parametric and hybrid methods are all relevant, noting that hybrid methods may provide more robust estimates in those high sea state and swell conditions that are less densely populated and where effects will be more significant. The development of SAR mode SSB corrections should include additional dependence on sea state development, which would be consistent with the tendency in LRM towards three-parameters SSB models (e.g. Tran et al., 2010b; Pires et al., 2016). The challenges of calibrating and validating SAR mode SSB corrections are the same - i.e. no better, no worse - than for conventional altimetry. For SAR mode altimetry however, P-LRM offer a unique way of calibrating and validating SAR mode SSB against conventional altimetry by providing coincident range measurements that have been shown to be unbiased against conventional LRM. In the case of Sentinel-6/Jason-CS, interleaved SAR mode will deliver true LRM data that make it possible to tie the Jason-CS SAR mode mission to the long-term altimetric data record without the issues linked to the loss of precision seen for SAR burstmode P-LRM

Modeling Envisat RA-2 waveforms in the coastal zone: case-study of calm water contamination

Radar altimeters have so far had limited use in the coastal zone, the area with most societal impact. This is due to both lack of, or insufficient accuracy in the necessary corrections, and more complicated altimeter signals. This paper examines waveform data from the Envisat RA-2 as it passes regularly over Pianosa (a 10 km2 island in the NW Mediterranean). Forty-six repeat passes were analysed, with most showing a reduction in signal upon passing over the island, with weak early returns corresponding to the reflections from land. Intriguingly one third of cases showed an anomalously bright hyperbolic feature. This feature may be due to extremely calm waters in the Golfo della Botte (northern side of the island), but the cause of its intermittency is not clear. The modelling of waveforms in such a complex land/sea environment demonstrates the potential for sea surface height retrievals much closer to the coast than is achieved by routine processing. The long-term development of altimetric records in the coastal zone will not only improve the calibration of altimetric data with coastal tide gauges, but also greatly enhance the study of storm surges and other coastal phenomena

Coastal altimetry products in the Strait of Gibraltar

This paper analyzes the availability and accuracy of coastal altimetry sea level products in the Strait of Gibraltar. All possible repeats of two sections of the Envisat and AltiKa ground-tracks were used in the eastern and western portions of the strait. For Envisat, along-track sea level anomalies (SLAs) at 18-Hz posting rate were computed using ranges from two sources, namely, the official Sensor Geophysical Data Records (SGDRs) and the outputs of a coastal waveform retracker, the Adaptive Leading Edge Subwaveform (ALES) retracker; in addition, SLAs at 1 Hz were obtained from the Centre for Topographic studies of the Ocean and Hydrosphere (CTOH). For AltiKa, along-track SLA at 40 Hz was also computed both from SGDR and ALES ranges. The sea state bias correction was recomputed for the ALES-retracked Envisat SLA. The quality of these altimeter products was validated using two tide gauges located on the southern coast of Spain. For Envisat, the availability of data close to the coast depends crucially on the strategy followed for data screening. Most of the rejected data were due to the radar instrument operating in a low-precision nonocean mode. We observed an improvement of about 20% in the accuracy of the Envisat SLAs from ALES compared to the standard (SGDR) and the reprocessed CTOH data sets. AltiKa shows higher accuracy, with no significant differences between SGDR and ALES. The use of products from both missions allows longer times series, leading to a better understanding of the hydrodynamic processes in the study area

Marine safety and data analytics : vessel crash stop maneuvering performance prediction

Crash stop maneuvering performance is one of the key indicators of the vessel safety properties for a shipbuilding company. Many different factors affect these performances, from the vessel design to the environmental conditions, hence it is not trivial to assess them accurately during the preliminary design stages. Several first principal equation methods are available to estimate the crash stop maneuvering performance, but unfortunately, these methods usually are either too costly or not accurate enough. To overcome these limitations, the authors propose a new data-driven method, based on the popular Random Forests learning algorithm, for predicting the crash stopping maneuvering performance. Results on real-world data provided by the DAMEN Shipyards show the effectiveness of the proposal

First spaceborne observation of sea surface height using GPS-reflectometry

An analysis of spaceborne Global Positioning System reflectometry (GPS-R) data from the TechDemoSat-1 (TDS-1) satellite is carried out to image the ocean sea surface height (SSH). An SSH estimation algorithm is applied to GPS-R delay waveforms over two regions in the South Atlantic and the North Pacific. Estimates made from TDS-1 overpasses during a 6 month period are aggregated to produce SSH maps of the two regions. The maps generally agree with the global DTU10 mean sea surface height. The GPS-R instrument is designed to make bistatic measurements of radar cross section for ocean wind observations, and its altimetric performance is not optimized. The differences observed between measured and DTU10 SSH can be attributed to limitations with the GPS-R instrument and the lack of precision orbit determination by the TDS-1 platform. These results represent the first observations of SSH by a spaceborne GPS-R instrument