Southern Ocean Wave Buoy – Update

In 2017, MetOcean Solutions partnered with New Zealand Defence Force and Defence Technology Agency to deploy a scientific wave buoy in the Southern Ocean. Moored 11 km south of the remote Campbell Island, the buoy collected 170 days of great data - including the May 2017 storm with a whopping 19.4 m wave! By July however, the perpetually rough seas caused fatigue in the mooring line and the buoy started on a new and rather intrepid journey toward Chile.

The buoy was launched on 2 March 2018.

“It is still sending us valuable data while drifting,” says oceanographer Dr Tom Durrant. “We are now seeing high quality wave measurements coming in from some of the remotest locations on Earth; it is extremely valuable data for our research.”

Meanwhile, the mission to collect wave data for NZ Navy’s SubAntarctic applications continues, and this year’s initiative has seen another wave buoy positioned at Campbell Island. This is New Zealand’s southernmost estate and an ideal spot to sample the complex directional wave spectra from the Southern Ocean. On 2 March 2018, MetOcean Solutions manager and senior oceanographer Dr Peter McComb led the buoy deployment from the Offshore Patrol Vessel HMNZS WELLINGTON, with support from Sally Garrett and William Coldicutt from the Defence Technology Agency.

Offshore Patrol Vessel HMNZS WELLINGTON.

“The crew of HMNZS WELLINGTON undertook the task with utmost professionalism and detailed planning to ensure a safe and successful execution,” says Peter. “In 2.5 m seas and light winds, the new wave buoy and its mooring were carefully placed at the same site as last year.”

This year however, the mooring design has been modified to better suit the harsh conditions and reduce the risk of mooring failure before the servicing mission next summer.

“We have to find the right balance for robustness in the mooring system while maintaining scientific integrity of the data. It is certainly a challenge working in these southern latitudes,” admits Peter. “But every month of data adds significantly to our knowledge of this ocean basin, so it’s a very worthy challenge”.

All data from the wave buoy programme is openly available for research, and interested members of the public can check the Southern Ocean wave conditions in real-time at http://www.metocean.co.nz/southern-ocean.

Forecasting Gita - extreme storm surge and wave heights

When tropical storm Gita passed over New Zealand on 20-21 February this year, high winds and low pressures combined with energetic ocean swells caused significant storm surges along the New Zealand West Coast.  

Storm surge is the abnormal rise of water generated by a storm, over and above the predicted astronomical tides. When accompanied by high waves, this surge can cause significant damage to coastal areas, including flooding and accelerated erosion.

“The storm offered an opportunity to validate our inhouse wave and surge models,” explains Dr Séverin Thiébaut, senior oceanographer at MetOcean Solutions. “Validation is when we compare the model results directly with in situ measurements, and provides us with a clear indication of how good our models are at predicting the timing and the magnitude of extreme storms. For Gita, we used data from a tide gauge at Charleston on the West Coast and a wave buoy in offshore south Taranaki.”

The forecast model predictions of storm surge and wave height during the storm are shown in Figures 1 and 2, respectively. Modelled wind and rainfall are also presented in these figures. These operational models are produced by MetOcean Solutions for a range of applications in NZ waters. The models are tuned to replicate the typical conditions, so verifying the predictions under an extreme storm is a powerful test.

Figure 1: Predicted storm surge progress: wind and rain (left) and storm surge (right) coincide as tropical storm Gita passes over New Zealand.

Figure 2: Predicted wave progress: wind and rain (left) and wave height (right) forecast as tropical storm Gita passes over New Zealand.

In Figures 3 and 4 we present the time series comparison of measured and forecast storm surge and wave heights.

“The test shows our model slightly underestimated the storm surge as measured by the nearshore tide gauge,” continues Séverin. “This is likely due to the geometry of the small bay where the tide gauge is located plus the effects of wave setup on the measured water levels. Near the shore, waves will produce a localised increase in water level, which magnifies the observed storm surge. However, we are delighted the timing of the predictions was good and the magnitude acceptable for an open-coast extreme.”

“The Charleston tide gauge was located on the margin of the main storm surge effect; the model predicted coastal water level elevations up to 0.50 m in the northern parts of the South Island but unfortunately no open coast tide gauges are located in that area.”

Figure 3: Time series of the storm surge as measured by the Charleston tide gauge data (Source: LINZ) and the MetOcean Solutions forecast values. The tide gauge reads higher values due to wave setup and the close proximity to shore.

“The comparison for offshore wave height was excellent for a such rapidly moving system. At the offshore wave buoy, the forecast timing and height of the waves were very well correlated with the measured storm values. The highest measured significant wave height was 8.8 m, while the forecast value was 8.4 m. “It is very encouraging to see the models perform with such confidence under these extreme storm conditions,” notes Séverin. “For context, the largest significant wave height ever recorded on the West Coast of NZ was 10.4 m, measured in May 1977 near the Maui A platform.”

Figure 4: Time series of the measured and modelled significant wave height at the offshore wave buoy (Source: OMV).

Through our web portal MetOceanView, MetOcean Solutions provide automated storm watch services for coastal and offshore operators. These are automatically generated when preset conditions are identified within the forecast horizon. During the lead up to Gita’s landfall, significant wave heights of 8-9 m were predicted more than 3 days ahead (Figure 5). Warnings are sent via email alerts for operational decision-making - increasing safety and efficiency for people working at sea. These warnings are based on an ‘ensemble’ of  forecasts of the winds and waves, which captures the inherent uncertainty over a 7-day forecast horizon and the chaotic nature of a revolving tropical storm. Probabilistic guidance allows effective management decisions to be made within a robust, quantitative framework.

Figure 5: Gita was forecast to be wild! Example of the ensemble forecast warning system that provided guidance on the range of possible outcomes for wind speed (top), significant wave height (middle) and wave direction (bottom) in the offshore Taranaki area.

MetOcean Solutions is a wholly owned subsidiary of state-owned enterprise, Meteorological Service of New Zealand (MetService). MetService is New Zealand’s national weather authority, providing comprehensive weather information services, to help protect the safety and well-being of New Zealanders and the economy.

For more information on our forecast models, contact us at enquiries@metocean.co.nz.

UK Ministry of Defence adopts SurfZoneView

The UK Ministry of Defence recently purchased an operational license for SurfZoneView, the New Zealand Navy software tool to support amphibious operations and beach landings.

New Zealand Defence Force amphibious operation (Image: Defence Technology Agency)

“Waves and currents make the surf zone a very dangerous environment,” explains Dr Rafael Guedes, senior oceanographer at MetOcean Solutions. “SurfZoneView provides high-resolution maps of the sea conditions in the surfzone, which helps determine the safest times and locations to offload equipment and personnel. This is crucial to the management of amphibious operations.”

Designed by MetOcean Solutions in partnership with the New Zealand Defence Force, SurfZoneView is based on the state-of-the-art XBeach numerical model. By resolving the main processes in this complex environment, the software clearly maps out the nearshore conditions and includes risk management tools to assist operational decision making.

“We are very pleased to supply our tool to one of the world’s largest defence forces,” says oceanographer Andre Lobato who manages the software updates. “It's great that the license also allows the tool to be used by the UK MetOffice for civilian purposes, such as search and rescue and beach safety analysis.”

The UK purchase coincides with the release of a new version of SurfZoneView.

“We had important feedback from amphibious units in Italy, UK, Australia and New Zealand. The new release incorporates a range of features requested by users after real training exercises,” continues Andre.

The tool clearly shows safe and unsafe zones for beach landings, and users can compare the relative safety of landing at different areas along a stretch of coastline, or at different times within a seven day forecast. Safety profiles allow users to test settings and examine how safety tolerances and vessel draughts alter the predictions.

In 2016, MetOcean Solutions won the Minister of Defence Industry Awards of Excellence for the SurfZoneView software. The uptake of the software by UK is further recognition of the value that accurate modelling, presented in a user-friendly format, can offer naval personnel operating in nearshore areas.

For more information on SurfZoneView, click here, or view the video for the 2016 award here.

Contact us on enquiries@metocean.co.nz for a trial version or demonstration of SurfZoneView.

Aitana Forcén-Vázquez heading to Antarctica

Aitana with the wave drifter buoys on board Tangaroa.

On February 9, Dr Aitana Forcén-Vázquez headed to Antarctica aboard the research vessel Tangaroa on a six week science voyage with colleagues from NIWA and the University of Auckland.

Aitana’s role as Principal Investigator for Physical Oceanography is to support instrument deployment and data collection, including the deployment of 9 drifting wave buoys for MetOcean Solutions and the New Zealand Defence Technology Agency.

“I am delighted to be part of this important voyage,” says Aitana. “I have been to Antarctic waters once  before, but this time we are going much closer to the continent, which will make for a very interesting trip.”

Tangaroa leaving Wellington on 9 February 2018.

The research project, entitled ‘Taking the pulse of the Ross Sea outflow’ focuses on collecting data to further the understanding of water movement between the shallow shelf and the deeper ocean. How the Ross Sea outflow changes over time is important for our understanding of future Southern Ocean and South Pacific climate.

During the voyage, Aitana will contribute to the mission blog, which can be found at www.oceanphysicsauckland.co.nz

Perfect storm caused Nelson flooding

On February 1, Fehi caused storm surges along New Zealand’s west coast, impacting coastal communities in many locations around the country. In Nelson whole streets were flooded in low-lying areas, causing emergency services to evacuate residents. Coastal residents were also evacuated in other areas including Taranaki and West Coast.

“The flooding was caused by an unlucky combination of factors,” explains oceanographer Dr Rafael Soutelino. “A very low pressure system coincided with king high tides, large waves and strong winds, resulting in very high coastal water levels in several areas around the country’s west coast.

“Storm surges occur when the sea rises as a result of wind and atmospheric pressure changes associated with a storm. The surges build up over time and will worsen when a low pressure system lingers.

“On this occasion, our models predicted a storm surge of up to 50 cm in Hokitika, and just over 35 cm in the Nelson region. This may not sound like much but when added to a king tide the impact can be devastating. The wind direction is important too. In this event, the trajectory of the tropical storm caused north-northeasterly winds which acted to push water towards the shore, further raising coastal sea levels.  

Storm surges of up to 35 cm above astronomical tide coincided with high winds in Nelson on 1 February 2018.

“Strong winds are common along the west coast of the South Island, but systems like Fehi that have tropical origin cause a much bigger pressure drop than normal winter storms. Such pressure drops cause sea level to rise, a phenomenon known as the inverse barometer effect.

“Storm surges of up to 50 cm are not unusual in New Zealand, and thankfully they most often do not coincide with king tides. However, occasionally the worst possible combination of events will occur, and at such time good forecasting become very important.”

Storm surge forecasts can predict dangerously high water levels up to seven days in advance, providing valuable alerts for for low-lying coastal locations. MetOcean Solutions frequently collaborates with emergency services and local authorities to provide forewarning when large storm surges are predicted.  

“Storm surges can be reliably predicted,” continues Rafael. “MetOcean Solutions forecasts storm surges nationwide using a complex high definition 3D hydrodynamical model with 5 km resolution.The model computes the atmospheric effects on coastal water levels. It combines this with baseline water levels generated by open ocean eddies and water column expansions and contractions caused by the spatially variable vertical density distribution.

“Waves also significantly modify water levels and consequent impacts of storm surges. We are currently working on improving our models to include waves in storm surge predictions for vulnerable locations around New Zealand. Hopefully such models will contribute towards keeping coastal communities safe when the next perfect storm hits.”

The 35 cm storm surge coincided with king tides and winds pushing water ashore, resulting in widespread flooding in Nelson.

Research partnership helps ocean industries

MetOcean Solutions and the Coastal and Regional Oceanography Group in the School of Mathematics and Statistics at the University of New South Wales (UNSW) are partnering to ensure that marine industries will benefit from the latest ocean research along the southeast coast of Australia.

“The science team at UNSW produces world-class research. By combining their ocean data and models with MetOcean Solutions’ operational experience we will provide an even better service for clients along the New South Wales coast,” says Prof Moninya Roughan, MetOcean Solutions' Chief Scientist and UNSW`s Coastal Oceanography Group Leader. “This collaboration helps make oceanographic research useable, making valuable knowledge easily accessible to marine industries and the public, and improving safety and efficiency at sea.”

The UNSW team developed a 23-year (1994-2016) hydrodynamic hindcast model using the 3D Regional Ocean Modeling System (ROMS). The model simulates ocean circulation at sufficient resolution (2.5-6 km) to characterise the hydrodynamics in the region. Results have been validated with quality, long-term oceanographic data, and were distributed through the Australian Integrated Marine Observing Program (NSW-IMOS).

The MetOcean Solutions team use model output to generate statistics needed by clients for design purposes. In addition they have characterised the coastal marine environment at a number of locations along the coast of SE Australia, and are conducting research that will improve understanding of dynamical drivers of the coastal circulation. The data has also been used to provide boundary conditions to clients for further downscaling studies.

Model domain and bathymetry showing the East Australian Current and the Tasman Front (Image by Kerry et al, 2016)

“Using the UNSW regional model ensures we are providing the highest quality information for our clients,” says MetOcean Solutions Forecast Operations Manager Dr Rafael Soutelino. “We are very enthusiastic about working with UNSW, and all the improvements we can achieve for industries and governments operating at sea in the region.”

UNSW`s oceanography group has been studying the East Australian Current (EAC) for decades, collecting valuable in-situ data and developing a suite of high-resolution numerical ocean models for the region. The EAC is the Western Boundary Current of the South Pacific subtropical gyre that flows south along the east coast of Australia, dominating the coastal circulation from Brisbane to Tasmania.

“The EAC is characterised by high eddy variability and the correct representation of these eddies into nearshore hydrodynamic models is critical,” says Dr. Colette Kerry, Postdoctoral Research Associate in the School of Mathematics and Statistics at UNSW. “Advancing our understanding of the dynamics of the EAC will help improve model predictions.”

For further information about Australian oceanographic research and consultancy services, please contact Alexis Berthot in Sydney at a.berthot@metocean.co.nz.

Wind pattern affects the sea surface temperature around the New Zealand coast

“Persistent northeast sector winds are forecast to change the sea surface temperatures around New Zealand this coming week,” says MetOcean Solutions senior oceanographer, Dr Rafael Soutelino.

“Gisborne, Coromandel, and parts of Northland will have the surface water transported offshore, and replaced by cooler waters from depths,” explains Rafael. “Indeed a 3 degree drop to a chilly 16°C is expected in Gisborne by 19 January. Meanwhile, on the West Coast we will see the opposite effect, with further warming of the water near the shore. Raglan may see temperatures rising again to as high as 23°C in the next week. That’s 3 degrees above the average for January.”

“Other places like Bay of Plenty will have slight onshore flows, which will maintain the warm coastal waters,” he adds.

The predicted winds and sea surface temperatures (left), and forecast graph (right) show the predicted sea surface temperatures at some coastal locations around New Zealand.

The sea surface temperature forecasts are produced by the MetOcean Solutions Regional Ocean Modelling System (ROMS). For more information, contact us at enquiries@metocean.co.nz.

An Open Data Discussion

By Peter McComb and Malene Felsing

What are open data?

The New Zealand government defines open data as data that anyone can use and share - data which have open licences, are openly accessible and are both human- and machine-readable¹.

Following the example of numerous countries, in August 2017 the New Zealand government adopted the International Open Data Charter, a non-binding agreement mandating that government data are open and accessible to all. The Open Data Charter builds on the New Zealand Declaration on Open and Transparent Government and the Data and Information Management Principles, through which the government has communicated an expectation that agencies proactively release high-value data, and work towards an ‘open by default’ approach².

These policies were adopted based on evidence from overseas that open data enables the development of new knowledge, tools and services, which drive economic development.

Benefits of open data

Since the inception of the term ‘open data’ in 1996, and the concurrent explosion of the internet and the movement towards open source code, the benefits of open data have been assessed by many. The results of the research show that data create more value when they are widely utilised and well-governed.

The clear benefits of open data include:

• Increased innovation as data become accessible to users from different disciplines.
• Reduced barriers to entry into markets.
• Creation of economic value through the development of new products, services or activities.
• Efficiency gains in the public sector as agencies gain access to data that help streamline operations, and through non-duplication of data collection efforts.
• Improvement in efficiency and productivity of private businesses using the data.
• Flow-on effects as emerging second-order users add further economic and social benefits to the economy.
• Increased government tax revenue through expanded economic activity, as well as higher revenue for individual agencies through the sale of high-value information to companies.
• Public engagement as the wider population can access educational and cultural knowledge.
• Improved social welfare as society benefits from transparent and accessible information, stimulating collaboration, participation and social innovation.
• Greater transparency and accountability of public service providers.
• Better policy-making based on better data.

There are numerous examples of international macroeconomic studies into the economic impact of open government data. A 2014 report³ assessing the value of open data for G20 economies predicted an AU$19 billion return on investment over five years from doubling the accessibility and use of Australian government and research data.

Who benefits the most?

Most analyses agree that open data benefits everyone - there are no real losers and widespread wins, because open data makes better use of existing resources. Consumers and the broader society stands to win the most, although there are some benefits to data providers. A European Union study⁴ concluded that releasing public sector information leads to modest direct revenues to governments. It estimated that most European nations would see a gain of 1% of agency budget, but that gains of up to 25% were possible. These estimates were based on the Netherlands and the UK, who both gather revenue from opening up government data. However, all studies agree that that open data creates new types of businesses, providing opportunities for small and medium enterprises and business models like advertiser-pays rather than end-user-pays⁵.

Open weather data

Of all the different types of public sector data, weather data have been identified as particularly important because everyone - including individuals, private companies, local and national government departments - can all benefit from it. Applications that make use of open weather data can therefore potentially have a huge impact.

Several studies have attempted to place a value on open weather data. Research from 2009⁶ indicated that US adults used more than 300 billion forecasts per year at the time, which was valued (by the general public) at $286 per household per year, providing an aggregate annual valuation of weather forecasts of about US$31.5 billion. At the time, government and private sectors spent US$5.1 billion on meteorological operations, research and forecasting, which means that the value provided by weather forecasts was 6.2 times higher than the cost of producing them.

Open weather data in New Zealand?

This is a really good question for New Zealand to ponder during 2018. We have a small economy with a big ocean to manage and we tend to get a lot of weather! There are two state-funded organisations independently collecting data and independently producing high quality national weather forecasts, plus a range of international weather forecast providers with various types and qualities of data available. So, what is our current source of weather truth? Is there a better way for the needs of the New Zealand economy and general public to be served? To answer that question in a meaningful way, it’s helpful to consider where exactly data comes into the equation.

The value ladder for society starts with data. We need open data so that all sectors of the economy can contribute to the generation of information and knowledge, so ultimately we can collectively and consistently make wise decisions.

This figure shows that data is the start of an entire value chain that takes society to a place where we can (hopefully) make wise decisions. In weather forecasting, data is both the observations and the model outputs. However, ‘data’ by itself is nearly useless to people, but when we turn it into ‘information’ such as a map or a graph, we create value because the data gains context. ‘Knowledge’ comes about when that information can be put to use, such as a warning of potentially hazardous conditions developing. It is situational awareness and requires prior experience or empirical findings. Finally, ‘wisdom’ is the place we want to get to in society, and modern-day tools like social media, smartphones and web sites allow us ready access to knowledge in its myriad of forms. The wise decisions we expect individuals to make are ones like:

               “I’m not going fishing today because the bar crossing might become dangerous.”
               “The conditions for climbing the peak are perfect tomorrow, so let's wait one more day.”
               “Better move the stock out of the river paddock because it's likely to flood tonight.”

Traditionally, the creation of weather knowledge has required human intervention, with trained forecasters interacting with data to produce guidance. As numerical weather models become better and more detailed weather measurements become available, the ability for models to accurately quantify and predict the weather will continue to improve. Weather on planet earth is still a chaotic process, however combining computer weather models with machine learning and other such techniques will allow us to become more quantitative when describing the present and future weather states.

And quantitative data is exactly what modern infrastructure demands. Think automated smart irrigation systems, traffic management algorithms and transport logistics networks to name just a few. All require weather data in the raw form to ingest and create information and knowledge specific to those applications. The global market for this is enormous, which is why private sector worldwide has invested so heavily in weather prediction and a whole new generation of sensing technologies. Within a few years the capability of private weather services will likely exceed that of most national weather agencies. Couple that with the disruption from constellations of small low cost weather satellites, and we have the imminent arrival of a new world order in weather forecasting.

What next?

So, back to data. New Zealand doesn’t have a great track record when it comes to making public funded environmental data openly available - but it's true we are making steady progress (see here). At the same time, the quantitative demands of the modern world are resulting in a flood of high quality private data becoming available and strong consumer options regarding alternative weather sources. In order to remain relevant, it might be timely for New Zealand to clearly define the national weather ‘sources of truth’, and perhaps actively push data into the economy to gain the universally benefit from the wealth multipliers that arise when enterprise creates knowledge from data.

Note - these are views of the authors, and do not represent MetOcean Solutions or MetService.

____________________

1. https://www.data.govt.nz/toolkit/what-is-open-data/
   
2. https://www.data.govt.nz/assets/Uploads/Adoption-of-the-International-Open-Data-Charter.pdf
   
3. Omidyar Network (2014) Open for Business: How Open Data Can Help Achieve the G20 Growth Target https://www.omidyar.com/sites/default/files/file_archive/insights/ON%20Report_061114_FNL.pdf
   
4. Vickery, G. (2011) Review of recent studies on PSI re-use and related market developments. European Commision. Available at: https://ec.europa.eu/digital-single-market/news/review-recent-studies-psi-reuse-and-related-market-developments
   
5. Deloitte (2011) Pricing of Public Sector Information Study (POPSIS) - Models of supply and charging for public sector information (ABC) - final report. Available for download at: https://ec.europa.eu/digital-single-market/en/news/pricing-public-sector-information-study-popsis-models-supply-and-charging-public-sector
   
6. Lazo, J.K., Morss, R.E., and J.L. Demuth (2009) 300 Billion Served: Sources, Perceptions, Uses, and Values of Weather Forecasts. Bulletin of the American Meteorological Society. 90(6).
   

Support for the New Zealand Ocean Data Network

MetOcean Solutions is delighted to support the New Zealand Ocean Data Network (NZODN), a new initiative coordinated by the National Institute of Water and Atmospheric Research (NIWA) to make New Zealand ocean data discoverable and freely available to all.

The NZODN is a national data platform that supports integrated access to marine and climate science data. NIWA has set up the NZODN as a node of the Australian Ocean Data Network (AODN) fully built on the services stack designed by the Australian Integrated Marine Observing System (IMOS).

The NZODN website has been launched as a public New Zealand resource, a ‘sister site’ to the AODN portal. This platform will greatly enhance data discovery and provide access to all available marine data collected in the New Zealand ocean domain.

Find out more about the New Zealand Ocean Data Network at https://nzodn.nz

MetOcean Solutions holds an extensive historical ocean database and is working towards quality control, formatting and documentation of these data so that they can be made publicly available through the NZODN infrastructure.

“We are very excited by the NZODN initiative. It is an important step for an integrated open data network that can be used by New Zealand's scientists and data-users,” says Prof Moninya Roughan, MetOcean Solutions' Chief Scientist. “It will greatly enhance the exchange of oceanographic knowledge and information, supporting ocean research and development of operational ocean services for NZ.”

IMOS Director Tim Moltmann says, “This is a major milestone for the collaboration between the two nations. The New Zealand Ocean Data Network Portal and our AODN portal complement each other, which allows for future strengthening of the collaboration in this region.”

Click here to access the datasets available at New Zealand Ocean Data Network or to find out more about how to contribute data.

Jorge Perez joins MetOcean Solutions

We are very pleased to welcome Dr Jorge Perez to MetOcean Solutions. Jorge is a physical oceanographer and will be working in our science team in Raglan. In his role, he will work on improving wave hindcasting and forecasting capabilities at Metocean Solutions.

Following an MSc in Coastal and Port Engineering, Jorge completed a PhD in Physical Oceanography at the University of Cantabria, Spain. His research has focused on wave climate, including a wide range of temporal and spatial scales.

With almost 10 years of experience in wave dynamics, Jorge has participated in a broad variety of projects, developing innovative solutions for statistical downscaling methods, wave tracking algorithms, and climate change projections. In his last research position he managed wave climate databases and generated wave historical data.

“Metocean Solutions makes top quality data easily accessible, removing the gap between advancements of research and final users,” says Jorge. “I am happy to join the team and participate in this exciting development”.

Tracking a lost sailing yacht

At the end of October, MetOcean Solutions helped an insurance company find a missing yacht that had been drifting for weeks in the Atlantic Ocean.

Pantaenius, the global yacht insurance company, were trying to help find a yacht abandoned during the Mini Transat 6.50 race. This solo race across the Atlantic Ocean, held every two years, sees sailors brave the roughly 4000 miles from France to the Caribbean only stopping in the Canary Islands on the way.

Jolly Rogers adrift in the Atlantic.

The yacht was Jolly Rogers, a MINI 6.50 (a 6.5 m high-performance sailing vessel), which had been abandoned on 5 October off Spain’s Cape Finisterre when persistent technical issues caused the sailor Luca Sabiu to set off his distress beacon. Luca was airlifted out by helicopter by the Spanish navy, leaving Jolly Rogers adrift.

The yacht was considered lost at sea until a sighting on Friday 20 October provided a position when preparations were made to start a salvage operation. The weather was closing in, however, with forecasts promising strong winds and wave heights in excess of 6 m. Worried that the boat would have drifted too far to be found by the time the weather settled down, Olivier de Roffignac from Pantaenius contacted MetOcean Solutions for advice on where the boat would drift to over two to three days of high winds and heavy seas.

“Searching for a 6 m sailboat in the Atlantic Ocean is a bit like looking for a needle in a haystack,” explains MetOcean Solutions’ oceanographer Simon Weppe, based in France.  “Salvage operations are costly, and Pantaenius wanted guidance on the likely drift track of the boat so that they could narrow down the search radius when the weather was calm enough to initiate the search.”

“To help Pantaenius we modelled the predicted drift of the vessel, continuously updating our predictions as new forecast cycles became available. To account for the uncertainties in the drifting behaviour of the boat, we ran simulations affording different importance to windage (wind-related drifting).

“The global models differ somewhat, and so to get the best results we used several different forecast datasets for winds and currents: the European Centre for Medium-Range Weather Forecasts (ECMWF) winds and MERCATOR currents*, and the US National Oceanic and Atmospheric Administration (NOAA) Global Forecasting System (GFS) winds and Real-Time Ocean Forecast System (RTOFS) currents.

Jolly Rogers was found only a couple of miles from the predicted location when using ECMWF winds and MERCATOR currents.

“We found a large variability in the predicted tracks depending on which current data we used. In this location, MERCATOR currents and the ECMWF winds yielded the best predictions. The salvage operation was launched on Monday 23 October, and the yacht was found 2-3 miles from the location we predicted, which is very encouraging given the many uncertainties.

“In this case, getting the current-related component of the drift was important because the yacht had sails and rigging dragging in the water, which would have acted as a sea anchor. In that region of the world, the MERCATOR currents are obviously more accurate than the RTOFS ones”.

The case highlights the importance of using several data sources and drifting model setups for situations where there is limited data on the drifting characteristics of the object lost.

Our team of experienced modellers is able  to quickly simulate the drifting trajectory of anything lost at sea - including vessels, personnel, and oil spills. By using different global datasets we can model a suite of possible trajectories, and compare the outputs, providing the best possible guidance for our clients.

“In the past, we have assisted clients by modelling the trajectory of oil spills, the spread of invasive species, and the dispersal of rubbish in the ocean. It is great that we could assist Pantaenius find the yacht.”

For more information about how we can assist with trajectory modelling, contact us at enquiries@metocean.co.nz.

* All MERCATOR current datasets (and more) can be accessed freely via The Copernicus Marine Environment Monitoring Service. The Copernicus Marine Environment Monitoring Service provides Full, Free and Open Access to Data & Information related to the Global Ocean and the Marine Environment.

Modelling the effects of dredge spoil disposal

As port weather experts, MetOcean Solutions regularly provides modelling support for port dredging operations. 

“The disposal of dredge spoil requires careful consideration,” explains Oceanographer Simon Weppe. “Over time, disposed sediments will be redistributed by currents and waves. When selecting offshore disposal sites, ports have to consider the hydrodynamic processes of the area and evaluate the longer-term changes to the shape of the seabed (morphological changes). Understanding the general morphological behaviour of the region is essential if we are to reduce the potential for sediment recirculation in the channel and port.

“Through our work with numerous ports, we’ve developed a process for modelling the effects of dredge spoil disposal. The changes to the shape of a disposal mound are governed by long-term hydrodynamic patterns slowly transporting sediments, and by extreme events such as storms, which can drastically change the shape of the seabed over short timescales. We use a coupled wave, current, and morphological model system, Delft3D, to understand the processes governing sediment transport in the area, and to identify key transport pathways. This gives us information to help predict the expected long-term morphological changes, as well as those arising from extreme events.”
 

Morphological changes predicted at the end of an accelerated 1-year simulation. A positive magnitude indicates sedimentation. The black polygons show the proposed disposal grounds and channel.

The Delft3D modelling system is placed within broader regional wave and 3D hydrodynamic models of the area. 

For waves, a 10-year historical data set (hindcast) is prepared using the Simulating WAves Nearshore (SWAN) model, carefully downscaled from a New Zealand-wide model to the high-resolution location domain. 

For currents, the Regional Ocean Modelling System (ROMS) is used to create a 10-year hydrodynamic hindcast using a three-step nesting approach, transferring the energy from a New Zealand-scale domain to a high-resolution local domain. 

The Delft3D model is used to simulate coupled wave, current and sediment transport. The modelling system uses boundary conditions from the regional wave (SWAN) and hydrodynamic (ROMS) models.

“Sediment transport depends on the particle size,” continues Simon. “To accurately predict the dispersal of sediments from the disposal site, we need reliable sediment grain size information. The settlement of larger particles, such as sandy sediments, is governed by gravitational forces, whereas for very fine sediments like silts and clays, inter-particle forces caused by ionic charges become significant. 

“When applying process-based models to predict morphological evolution, the main challenge is that the morphology of coastal systems develops over time scales several orders of magnitude larger than the time scale of the hydrodynamic fluctuations responsible for sediment transport, i.e. hours to days versus years to decades, and more. This means that a model system that can predict the time series of instantaneous hydrodynamics and sediment transport will require an unfeasibly long period to compute a multi-year real-time simulation. 

“To overcome this, we use the Morphological Acceleration Factor (MORFAC) method. MORFAC combines the reduction of the input forcing with the use of morphological factors. This means that we reduce the ambient wave and hydrodynamic forcings to a set of representative conditions that reproduce the same morphological evolution as the real-time forcing would. We do this by combining representative wave events with representative tides and current patterns for the site. 

Morphological Acceleration Factors (MORFACs) are used to represent the long-term effects of tides and waves on the seabed morphology within morphological models. Adapted from Ranasinghe et al. (2011).

“To account for long-term sediment movement as well as that resulting from storms, we generate two types of results: annual morphological simulations and historical storm simulations. The annual simulations provide information on the net sediment dispersion around the disposal mound each year. The real historical storm simulations model the detailed wave, circulation and sediment transport patterns that develop during energetic events, which normally cause the most significant morphological changes.

“Our modelling provides a best estimate of sediment dispersal from the disposal site over time, taking into consideration both day-to-day currents and waves and storm conditions which move large amounts of sediment in one go. The actual sediment transport may differ slightly depending on the timing of storms, but the overall pattern of sediment movement will remain valid. 

“Regulators use the information to determine the potential effects of the dredge disposal on local hydrodynamic processes, and to ensure there is minimal impact on sites of particular ecological or amenity value. Knowing where sediments will end up helps the mitigation, monitoring and management of dredging operations.”

For more information on dredge disposal modelling, contact us at enquiries@metocean.co.nz.
 

Mean wave, current velocity and sediment transport fields for a disposal site for Lyttelton Port off the Canterbury coast in New Zealand. The black polygons show the proposed disposal grounds and channel.

Drifting wave buoy caught in Southern Ocean eddy

The drifting Southern Ocean Wave Buoy is going round in circles deep in the Southern Ocean, temporarily slowing down its steady passage east across the southern margin of the Pacific. 

The buoy is caught in an eddy, a circular movement of water created when a bend in a surface ocean current pinches off to make a loop, which separates from the main current. 

The buoy, which has been drifting with the ocean currents since it left its moored location on 28 July, was deployed south of Campbell Island in February 2017. Part of a collaborative research project involving the Defence Technology Agency and MetOcean Solutions, the buoy has been transmitting wave spectra data via a satellite link, providing vital information which will help the New Zealand Defence Force to design patrol ships suited to the rough seas of the Southern Ocean. 

In the two and a half months since its escape, the buoy has drifted some 450 nautical miles east-northeast. In late September, the buoy passed within 20 nautical miles of the remote uninhabited Antipodes Island group.

Senior Oceanographer Dr Peter McComb is happy that data is still being transmitted. "The buoy is solar powered, and we were expecting the batteries to run out during the subantarctic winter. However, it is still happily sending wave spectra data from its path drifting slowly eastwards along the southern margin of the Pacific Ocean. So far, it has encountered moderately rough seas, with significant wave heights of up to 9 m and maximum wave heights of 15 m. 

"The prevailing winds and ocean currents in this region are towards the east, however, the buoy track meanders significantly as the drift is influenced by ocean eddies within the Antarctic Circumpolar Current. The average drift speed is about 1 km per hour, but the net eastward drift is about half that. The buoy has been trapped in an eddy for the last three weeks, resulting in almost no net drift. The eddy is unlikely to last long, and the buoy will soon be released and continue drifting east. From now on, there are very few islands in the way - if it continues due east at the current speed, it will get to the west coast of South America in about a year and a half. However, a strong southerly blow in the next few weeks could push it north toward the Chatham Islands, and if that happens we might launch a recovery mission.”  

In May 2017 the buoy made headlines when it measured a monster 19.4 m wave from the moored location near Campbell Island. 
 

Meet us at the GODAE Ocean View Summer School

Prof Moninya Roughan sharing her ocean observation expertise.

This week, Prof Roughan is teaching at the GODAE Ocean View Summer School in Mallorca, Spain. GODAE is the Global Ocean Data Assimilation Experiment, an international initiative started in 1997 aiming to establish infrastructure for global operational oceanography. Prof Roughan is part of a team of world-leading oceanographers brought together in the summer school to teach the next generation of leading oceanographers, some 70 students from around the world. 

Prof Roughan is giving two lectures on ocean observing, covering global and coastal in situ observations. 

New Zealand aims to be a GODAE contributor within 1-2 years with the operational development of the Moana Project modelling hindcast / forecast suite, which will be greatly facilitated by MetOcean Solutions' new role as New Zealand's operational oceanography provider. Operational oceanography is an integrated approach using a variety of methods (including satellite observations, in situ monitoring, and modelling), science-based and user-driven to describe and forecast the ocean to support societal needs.

The participants of the GODAE Ocean View Summer School. 

MetOcean Solutions and MetService join forces

 
Today the Meteorological Service of New Zealand (MetService) acquired the final 51% of shares in MetOcean Solutions to become 100% owner. The acquisition is the result of more than four years of collaboration and planning, notes Managing Director Dr Peter McComb. ”This is the start of an exciting new phase for ocean science in New Zealand and the South Pacific,” he says. “For the first time, our country will have a cohesive national operational oceanographic capability. New Zealand is custodian of the 4th largest marine estate on the planet and that comes with a broad responsibility. The MetOcean Solutions science team has been building the expertise and resources to meet that need for the last 10 years, and now we are delighted the investment by MetService will allow the country and indeed the wider South Pacific region to realise those benefits. This means improved forecasting of waves, coastal currents, ocean temperature, storm surge and hazardous situations. Also, a rapid and reliable marine response capability in disaster situations like the MV Rena grounding will now be possible.”
 
CEO of MetService, Peter Lennox adds, ”The benefits go beyond national marine safety improvements; we see a future where exceptional weather services developed for our geography are exported to the world. The technologies developed by MetOcean Solutions are already well respected in overseas markets and with full partnership, the two organisations can more effectively leverage each other's strengths and bring the unique value of our Powerful Weather Intelligence to commercial opportunities worldwide.”    
 
MetOcean Solutions will continue to operate as a separate trading entity, maintaining the strong R&D pedigree of the past decade and adhering to its core principles of scientific integrity and technical elegance along with the ethos of ‘collaboration for success’.

Modelling support for port modifications

Over recent years, MetOcean Solutions has modelled the effects of dredging for ports all over New Zealand and Australia. 

Using models we can estimate the percentage of time suspended solid concentration thresholds (here 10 mg/L) are exceeded during dredge spoil disposal operations. Inner and outer dashed circles radius: 500 and 1000 m, respectively. 

“Port modifications and maintenance often involve dredging,” explains Project Director Dr Brett Beamsley. “This can include deepening channels or berth pockets, or maintaining existing depths.” 

“Over the years, we have developed modelling processes to support ports and regulators evaluate the impacts from, and manage, port dredging in the best possible manner.” 

Dredging can have complex effects. It causes sediment release and temporarily increased levels of suspended solids. Dredge spoil disposal changes the shape of the seabed at the disposal site, and deepening channels can alter the waves and tidal flows in nearby areas, potentially affecting structures such as wharves and jetties, as well as processes like shoreline erosion. 

Source of a dredge plume for a Trailing Suction Hopper Dredger. 1. Drag head; 2. Overflow; 3. Prop wash. After Becker et al. (2015).
 

The dispersal of sediments occurring during dredge disposal can be modelled.

Suspended solids can be harmful to marine life. To minimise adverse effects, managers need to know the extent and duration of suspended sediment plumes, and what levels of suspended solids to expect within the plumes. Because the plumes move with the water, hydrodynamic models can be used to predict their extent and duration.

Managers also need to know the effects of discharging sediment at offshore disposal sites. They need to ensure that dredge spoil is disposed at suitable sites, where potential changes to the seabed shape will not cause adverse effects on flow, tidal flushing and local wave climate, and that disposed sediments will not be carried to nearby areas of environmental or amenity importance.

MetOcean Solutions employs a multi-disciplinary team of scientists with a wide range of expertise in port studies and is therefore well placed to provide scientific advice to ports. Two of the company’s founding directors did PhD research on the wave and sediment dynamics at New Zealand ports.

“We use a variety of techniques to get the modelling spot on,” continues Dr Beamsley. “As a starting point, we collate all information we can find for the site, including any wave or current measurements. Additional field data is often collected to ensure that important flow dynamics are captured.” 

“Once we have enough data, we set up a series of models. First, we develop regional and local-scale wave and hydrodynamic models which capture important processes responsible for sediment entrainment and transport. We nest these into larger-scale wave and hydrodynamic models to ensure atmospheric forcing and river discharges are taken into account where necessary. We calibrate and validate the models against all available measured data.

“Once we’re satisfied our models are performing well, we generate a historical data set for the location, detailing wind, waves and currents for multiple years. This historical data set is used to define the wave and hydrodynamic climate of the site and is used as input into all subsequent studies.

“We simulate dredging plumes using models that track sediment particles as they disperse from the site of dredging. Dredging typically releases sediments near the seabed and just below the water surface. Following an initial near-field phase, dredge plumes move with current flows. Over time, the particulates settle out, with larger grain sizes settling faster and finer sediments being transported further, although flocculation needs to be considered. Through modelling the evolution of the plume over time, our oceanographers simulate the particulates as they settle on the seabed, and trace the levels of suspended solids that remain in the water column. 

Example of plume modelling, showing average near-seabed suspended solid concentrations (SSC) for Lyttelton Harbour, New Zealand.

“The dispersal of dredge spoil disposal is investigated using high-resolution morphological models, which account for the surficial sediment grain size within the disposal ground. Using these morphological model we simulate the development of the disposal ground over multiple years to decades, modelling how existing flow patterns will affect the disposal mound and how the mound will affect circulation. As part of this, we determine the likely length of time that discharged sediment resides at the offshore disposal ground and highlight sediment transport pathways, determining where the disposed sediments are likely to ultimately end up.”

After five years the disposed sediments at this site have dispersed. The figure shows the cumulative morphological changes after each year over a 5-year morphological simulation of the disposal of 18 million m3 sediment onto a 12.5 km2 disposal ground. Initial bathymetric contours are shown in black. A positive magnitude (yellow and red colours) indicates sedimentation.

For a discussion about how MetOcean Solutions can help you predict and manage the effects of your dredging operations, contact us at enquiries@metocean.co.nz.

Smart Ideas funding for MetOcean Solutions

MetOcean Solutions has received research funding for a project applying innovative technology to weather forecasting. The research, entitled ‘Machine learning for convective weather analysis and forecasting’, was funded in the Ministry of Business, Innovation and Employment (MBIE) 2017 Endeavour Round.

Led by MetOcean Solutions, the project is a collaboration with the Knowledge, Engineering & Discovery Research Institute (KEDRI) of Auckland University of Technology, and the New Zealand MetService.

“We are very pleased to receive funding for this exciting project,” states project lead Dr David Johnson.

The research will use machine learning to predict convective weather events. Convective weather produces heavy rain, lightning and strong winds, significantly impacting the safety, efficiency and well-being of New Zealanders, and recent severe events have caused loss of life and extensive damage to property.

“Convective weather is localised in time and space and can develop quite quickly and sometimes without much warning,” continues Dr Johnson. “These events are always associated with cloud masses - like big thunderstorm clouds - which can be seen from Earth-observing satellites. Currently, human forecasters detect these events by looking at satellite imagery, numerical model guidance, and rain radar. Trained forecasters are good at doing this, but humans cannot look everywhere all the time. Recent advances in machine learning mean that computers are now exceptionally good at identifying and labelling features in images. Our research will train a machine-learning algorithm to analyse satellite imagery, possibly combined with other inputs such as numerical model guidance or rain radar, and predict where and when heavy rain, lightning or wind squalls might occur. As this is a machine process it can potentially be fully automated and then used to send alerts on a phone app.

“There is a good chance that the algorithm will be better than a human at consistently making the correct predictions, which means that all New Zealanders will benefit from better weather forecasts. An automated forecasting system also allows for greater customisation and localisation for individual needs. If successful, the research could lead to apps that makes it possible for you to request a phone alert if heavy rain is likely at your location - your phone already knows where you are - allowing you to take in your washing, seek shelter or postpone your drive home. Many industries are weather-dependent, and accurate local forecasts of strong winds or heavy rainfall will help anyone working or organising events outdoors, including the forestry, fisheries, construction and transport industries, all of whom have different weather thresholds to ensure safety and efficiency. Human forecasters could never manage to serve all the myriad of end-user needs at different locations and times.

“The key to success is the collaboration with KEDRI, who are world-leading machine learning experts, and MetService who carry out day-to-day severe weather forecasts for New Zealand. MetOcean Solutions brings our track-record of applying state of the art science and technology to provide end-user tools and services.”

MBIE's 2017 Endeavour Round funded 68 new scientific research projects from 408 applications.

Click here for the MBIE press release on the funding.

Hauraki Gulf current hindcast now available

MetOcean Solutions recently completed a 26-year hindcast detailing currents and water elevation of the Hauraki Gulf. The hindcast was created using a 2-dimensional Regional Ocean Modeling System (ROMS) model run at 250 m resolution, delivering detailed depth-averaged currents and water elevation data from 1989 to 2016.

Oceanographer Phellipe Couto carried out the modelling. He explains: “The model resolves barotropic tides - the depth-averaged velocity component of the tide - as well as water levels. The Hauraki Gulf is subject to storm surges, which are driven by wind setup and atmospheric pressure. Low-pressure systems sweeping across New Zealand result in surge, which can act to amplify the tides, causing very low or high water levels."

Snapshots of modelled atmospheric and oceanic fields during a meteorological event. Upper panels show mean sea level pressure contours and non-tidal sea surface elevation provided by the New Zealand-wide grid. The animation at the bottom illustrates the depth-averaged current flow field inside the Hauraki Gulf reproduced in the high-resolution grid.

“To accurately resolve the tides and water levels inside the Gulf, we had to get the forcings right. We used high-resolution tidal constituents at the boundaries combined to fine resolution bathymetry constructed from available data, including data from nautical charts and independent surveys. We also ran a New Zealand-scale ROMS model at 5 km resolution to provide boundary conditions, allowing us to properly downscale energy and associated sea surface perturbations from the larger scales into the 250 m grid of the Hauraki Gulf model. For atmospheric forcing, we used the Hau-Moana data set - the 12 km resolution atmospheric hindcast for the New Zealand-wide domain, and the 4 km resolution Hauraki Gulf data for our higher resolution grid.”

The hindcast data was validated against water elevation data from a tide gauge at Tiritiri Matangi Island.  

“The validation shows good agreement between modelled and measured water elevation levels,” continues Phellipe. “The hindcast provides a robust baseline tide and water elevation data set for the area, outlining the prevailing conditions for use by people who operate within or manage the Gulf. The data can also be used as boundary conditions for higher resolution modelling of local areas within the Gulf, e.g. for the hydrodynamic modelling of estuaries or embayments. This study forms the foundation for developing a full 3-dimensional hydrodynamic model which will help with the management of water quality, and gain insight into transport (e.g. of larvae or sediments), dispersion, and flushing timescales in the Hauraki Gulf.”

For further information about the Hauraki Gulf ROMS hindcast, please contact enquiries@metocean.co.nz.     

Moana Project releases Hau-Moana: NZ atmospheric downscaling data

The first output from the Moana Project is available. The project team is pleased to release the Hau-Moana data set, the New Zealand atmospheric downscaling.

Project Leader Associate Professor Moninya Roughan is excited. “We are happy to have the first data product available already. The MetOcean Solutions team has been working hard to finish this first step of the Moana Project, paving the way for the work packages to come.”
 

Top panels show low-resolution atmospheric products available globally from CFSR. The lower panels show the benefit of increasing the resolution in an NZ specific context around regions of complex topography such as the Cook Strait. Higher resolution modelling increases the accuracy of the data.
 

Oceanographer Rosa Trancoso presented the project at the 2017 NZ Physical Oceanography Workshop in Wellington in mid-August. “Hau-Moana came about because we needed more accurate wind fields to improve our ocean modelling,” she explains. “The global Climate Forecast System Reanalysis (CFSR) made public by the National Center of Environmental Prediction, is used globally, however it does not provide accurate wind fields for nearshore areas, particularly around NZ. For accurate ocean modelling, atmospheric forcing needs to account for coastal topographic effects, shoreline complexity, and ocean surface temperatures. New Zealand is subject to rapidly moving weather systems, and complex topography, which means that we require atmospheric forcing data at good spatial and temporal resolution.

For the downscaling, the team used 0.312 degrees for sea surface temperature (SST) and surface fields such as pressure, humidity, temperature, etc. The modelling was done using 12-hour independent runs, discarding the first five hours to allow for model spin-up. 

The outputs were validated against data from 33 coastal sites around New Zealand and two offshore sites.

The model was validated using weather data from 33 coastal and two offshore observation sites.

“Overall, the validation shows the model to perform well,” adds Rosa. “This means that we now have a better atmospheric data set for New Zealand than we’ve ever had in the past. Hau-Moana version 1.0 is a first step towards a high-quality, high-resolution, long-term reference data set, which can be improved in the future. The dataset covers the period from 1979 to 2015, and we’re currently working on a comprehensive validation and a descriptive paper for publication in a scientific journal.”

NIWA Ocean Modeller Dr Mark Hadfield says that the Hau-Moana high-resolution wind field is a key component in improving modelled circulation in the Cook Strait.

The Hau-Moana data set is freely available upon request - contact us at info@moanaproject.org if you would like to access it. 

For more information about the Moana Project, visit the website: www.moanaproject.org. 

Higher-resolution atmospheric modelling improves modelling of waves and currents. Left-hand images show the CFSR and WRF model outputs for mean wind speed (m/s) (top) and mean significant wave height (m) (bottom); right-hand images show the difference between the two, with negative values in blue and positive values in red.

Modelling the dispersal and settlement of drill cuttings

Drilling operations at sea produce a mix of fine rock fragments that need to be discharged into the ocean. While inert, these fragments (known as drill cuttings) can have sediments, contaminants and drilling fluids adhering to them. To help regulators and marine managers assess the potential impact of drilling operations, MetOcean Solutions is regularly engaged to model the dispersal and settlement of drill cuttings in the marine environment at locations all over the world. 

“Drill cuttings settle on the seabed, where they can cause adverse environmental impacts,” explains Oceanographer Remy Zyngfogel. “The oceanic discharge of drill cuttings occurs over specific time periods, but their dispersal and deposition are driven by random variables such as currents and turbulence.” 

“To determine where the drill cuttings end up on the seabed, we use a variety of methods and leverage the expertise of our multidisciplinary science team. This includes modelling the hydrodynamics of the region and simulating the trajectory and the settling of the drill cuttings to the seabed. Regulators and marine managers require good knowledge of the likely footprint of  deposition and how thick the deposits will be at increasing distances from the drill site.”

Project Director Dr Brett Beamsley oversees the hydrodynamic modelling. “We use different models to produce the historical datasets needed for the studies,” advises Brett. “Oceanic and coastal currents vary according to synoptic and seasonal winds, tides and density differences. To account for this variability, and to provide robust statistical estimates of dispersal and deposition, we use historical data to recreate the actual oceanographic conditions, typically hour-by-hour for a 10-year period. We recreate these currents using the most appropriate model. For offshore studies, we use the Regional Ocean Modeling System (ROMS), whereas for smaller-scale studies at inshore sites SCHISM or Delft3D are used.” 
 

An example of 7-day mean surface current circulation and Sea Surface Temperature (°C) for the south-eastern region of Brazil.

Remy uses the historical current dataset to determine the dispersal of drill cuttings. “Once we have the historical currents, we use a particle tracking model to trace the dispersal and deposition of drill cuttings for simulated discharges at different times of the year,” he explains. “Ocean currents vary with factors like seasonal winds and riverine discharges, so the depositional footprint will differ depending on which time of year the drilling is done. The size of fragments discharged into the sea depends on the rock type and the drill bit design. From an estimate of particle size, we can determine settling velocities - the finest fractions of the drill cuttings settle through the water column very slowly and become widely dispersed, whereas larger particles settle quickly and much closer to the discharge location.”

Example deposition thickness for drill cuttings discharged from a marine location. The spatial distributions of deposition thickness are color-coded with values in mm on each contour line in four zoom views: 100x100 km (top left), 10x10 km (top right), 1x1 km (bottom left) and 100x100 m (bottom right). The release site is indicated as a black cross. 

“The modelling represents what is likely to happen statistically, over long time periods. Naturally, for any given discharge, the drill cuttings will disperse according to the flow conditions at the time. For example, if discharge occurs during high current flows, the drill cuttings will be transported further, and the deposition will be more spread out. If current velocities are low at the time of discharge, the cuttings will accumulate closer to the discharge point.” 

Where pre- and post-drilling sediment samples have been taken, it is possible to verify the dispersal modelling. 

“We often use barium as a tracer,” explains Remy.  “Drill cuttings contain elevated concentrations of barium from the drilling fluids. This makes barium an ideal tracer of discharged cuttings. Seabed samples taken before and after drilling can be used to determine the change in barium concentration and thereby verify the modelled deposition of the cuttings.“

“The modelling provides a statistical representation of possible outcomes, taking into account the natural variety of current flow conditions. The modelled results typically show good agreement with observed barium levels, which means that operators and regulators can confidently use the modelling to determine the extent of potential adverse effects. This information is used both when applying for permits and post-permit, in the design of environmental monitoring programmes.” 

Contact us if you would like to discuss modelling the discharge of drill cuttings or historical current data for your drilling location.