Synergy of wind wave model simulations and satellite observations during extreme events

In this study, the quality of wave data provided by the new Sentinel-3A satellite is evaluated and the sensitivity of the wave model to wind forcing is tested. We focus on coastal areas, where altimeter data are of lower quality and wave modelling is more complex than for the open ocean. In the first part of the study, the sensitivity of the wave model to wind forcing is evaluated using data with different temporal and spatial resolution, such as ERA-Interim and ERA5 reanalyses, the European Centre for Medium-Range Weather Forecasts (ECMWF) operational analysis and short-range forecasts, German Weather Service (DWD) forecasts and regional atmospheric model simulations (coastDat). Numerical simulations show that the wave model forced using the ERA5 reanalyses and that forced using the ECMWF operational analysis/forecast demonstrate the best capability over the whole study period, as well as during extreme events. To further estimate the variance of the significant wave height of ensemble members for different wind forcings, especially during extreme events, an empirical orthogonal function (EOF) analysis is performed. In the second part of the study, the satellite data of Sentinel-3A, Jason-2 and CryoSat-2 are assessed in comparison with in situ measurements and spectral wave model (WAM) simulations. Intercomparisons between remote sensing and in situ observations demonstrate that the overall quality of the former is good over the North Sea and Baltic Sea throughout the study period, although the significant wave heights estimated based on satellite data tend to be greater than the in situ measurements by 7 to 26&thinsp;cm. The quality of all satellite data near the coastal area decreases; however, within 10&thinsp;km off the coast, Sentinel-3A performs better than the other two satellites. Analyses in which data from satellite tracks are separated in terms of onshore and offshore flights have been carried out. No substantial differences are found when comparing the statistics for onshore and offshore flights. Moreover, no substantial differences are found between satellite tracks under various metocean conditions. Furthermore, the satellite data quality does not depend on the wind direction relative to the flight direction. Thus, the quality of the data obtained by the new Sentinel-3A satellite over coastal areas is improved compared to that of older satellites.</p

Robust wavebuoys for the marginal ice zone: Experiences from a large persistent array in the Beaufort Sea

An array of novel directional wavebuoys was designed and deployed into the Beaufort Sea ice cover in March 2014, as part of the Office of Naval Research Marginal Ice Zone experiment. The buoys were designed to drift with the ice throughout the year and monitor the expected breakup and retreat of the ice cover, forced by waves travelling into the ice from open water. Buoys were deployed from fast-and-light air-supported ice camps, based out of Sachs Harbour on Canada’s Banks Island, and drifted westwards with the sea ice over the course of spring, summer and autumn, as the ice melted, broke up and finally re-froze. The buoys transmitted heave, roll and pitch timeseries at 1 Hz sample frequency over the course of up to eight months, surviving both convergent ice dynamics and significant waves-in-ice events. Twelve of the 19 buoys survived until their batteries were finally exhausted during freeze-up in late October/November. Ice impact was found to have contaminated a significant proportion of the Kalman-filter-derived heave records, and these bad records were removed with reference to raw x/y/z accelerations. The quality of magnetometer-derived buoy headings at the very high magnetic field inclinations close to the magnetic pole was found to be generally acceptable, except in the case of four buoys which had probably suffered rough handling during transport to the ice. In general, these new buoys performed as expected, though vigilance as to the veracity of the output is required

A global ensemble of ocean wave climate statistics from contemporary wave reanalysis and hindcasts

There are numerous global ocean wave reanalysis and hindcast products currently being distributed and used across different scientific fields. However, there is not a consistent dataset that can sample across all existing products based on a standardized framework. Here, we present and describe the first coordinated multi-product ensemble of present-day global wave fields available to date. This dataset, produced through the Coordinated Ocean Wave Climate Project (COWCLIP) phase 2, includes general and extreme statistics of significant wave height (Hs), mean wave period (Tm) and mean wave direction (θm) computed across 1980–2014, at different frequency resolutions (monthly, seasonally, and annually). This coordinated global ensemble has been derived from fourteen state-of-the-science global wave products obtained from different atmospheric reanalysis forcing and downscaling methods. This data set has been processed, under a specific framework for consistency and quality, following standard Data Reference Syntax, Directory Structures and Metadata specifications. This new comprehensive dataset provides support to future broad-scale analysis of historical wave climatology and variability as well as coastal risk and vulnerability assessments across offshore and coastal engineering applications

The Sea State CCI dataset v1: towards a sea state climate data record based on satellite observations

Sea state data are of major importance for climate studies, marine engineering, safety at sea and coastal management. However, long-term sea state datasets are sparse and not always consistent, and sea state data users still mostly rely on numerical wave models for research and engineering applications. Facing the urgent need for a sea state climate data record, the Global Climate Observing System has listed “Sea State” as an Essential Climate Variable (ECV), fostering the launch in 2018 of the Sea State Climate Change Initiative (CCI). The CCI is a programme of the European Space Agency, whose objective is to realise the full potential of global Earth observation archives established by ESA and its member states in order to contribute to the ECV database. This paper presents the implementation of the first release of the Sea State CCI dataset, the implementation and benefits of a high-level denoising method, its validation against in situ measurements and numerical model outputs, and the future developments considered within the Sea State CCI project. The Sea State CCI dataset v1 is freely available on the ESA CCI website (http://cci.esa.int/data, last access: 25 August 2020) at ftp://anon-ftp.ceda.ac.uk/neodc/esacci/sea_state/data/v1.1_release/ (last access: 25 August 2020). Three products are available: a multi-mission along-track L2P product (http://dx.doi.org/ 10.5285/f91cd3ee7b6243d5b7d41b9beaf397e1, Piollé et al., 2020a), a daily merged multi mission along-track L3 product (http://dx.doi.org/10.5285/3ef6a5a66e9947d39b356251909dc12b, Piollé et al., 2020b) and a multimission monthly gridded L4 product (http://dx.doi.org/10.5285/47140d618dcc40309e1edbca7e773478, Piollé et al., 2020c)

Global ocean wave fields show consistent regional trends between 1980 and 2014 in a multi-product ensemble

Historical trends in the direction and magnitude of ocean surface wave height, period, or direction are debated due to diverse data, time-periods, or methodologies. Using a consistent community-driven ensemble of global wave products, we quantify and establish regions with robust trends in global multivariate wave fields between 1980 and 2014. We find that about 30–40% of the global ocean experienced robust seasonal trends in mean and extreme wave height, period, and direction. Most of the Southern Hemisphere exhibited strong upward-trending wave heights (1–2 cm per year) and periods during winter and summer. Ocean basins with robust positive trends are far larger than those with negative trends. Historical trends calculated over shorter periods generally agree with satellite records but vary from product to product, with some showing a consistently negative bias. Variability in trends across products and time-periods highlights the importance of considering multiple sources when seeking robust change analyses.publishedVersio

Global ocean wave fields show consistent regional trends between 1980 and 2014 in a multi-product ensemble

Historical trends in the direction and magnitude of ocean surface wave height, period, or direction are debated due to diverse data, time-periods, or methodologies. Using a consistent community-driven ensemble of global wave products, we quantify and establish regions with robust trends in global multivariate wave fields between 1980 and 2014. We find that about 30-40% of the global ocean experienced robust seasonal trends in mean and extreme wave height, period, and direction. Most of the Southern Hemisphere exhibited strong upward-trending wave heights (1-2 cm per year) and periods during winter and summer. Ocean basins with robust positive trends are far larger than those with negative trends. Historical trends calculated over shorter periods generally agree with satellite records but vary from product to product, with some showing a consistently negative bias. Variability in trends across products and time-periods highlights the importance of considering multiple sources when seeking robust change analyses

Strategies for simulating the drift of marine debris

Modelling the drift of marine debris in quasi-real time can be of societal relevance. One pertinent example is Malaysia Airlines flight MH370. The aircraft is assumed to have crashed in the Indian Ocean, leaving floating wreckage to drift on the surface. Some of these items were recovered around the western Indian Ocean. We use ocean currents simulated by an operational ocean model in conjunction with surface Stokes drift to determine the possible paths taken by the debris. We consider: (1) How important is the influence of surface waves on the drift? (2) What are the relative benefits of forward- and backward-tracking in time? (3) Does including information from more items refine the most probable crash-site region? Our results highlight a critical contribution of Stokes drift and emphasise the need to know precisely the buoyancy characteristics of the items. The differences between the tracking approaches provide a measure of uncertainty which can be minimised by simulating a sufficiently large number of virtual debris. Given the uncertainties associated with the timings of the debris sightings, we show that at least 5 items are required to achieve an optimal most probable crash-site region. The results have implications for other drift simulation applications