Dynamic Part of the Guide to Marine Emergency and Response (WMO-No. 1348)
DYNAMIC ANNEX TO THE GUIDE TO MARINE EMERGENCY RESPONSE
Authors: Bruce Hackett (Norwegian Meteorological Institute), Pierre Daniel (Météo-France) and Alice Soares (Portugal, WMO Consultant)
Marine emergency response (MER), including marine environmental emergency response (MEER) and search and rescue (SAR), refers to the process of responding to an emergency, related to drifting substances or objects in the water, usually the ocean, in national or international waters. This Dynamic Annex to the Guide to Marine Emergency Response (WMO-No. 1348) describes potential sources of data, tools and models: (1) geophysical forcing data required for drift prediction with regards to MER, (2) data and information for detection and monitoring of objects and (3) information on operational transport and fate models. This is a dynamic document noting that additional sources of information may emerge, as well as changes to the existing data, tools and models may result from technological and science developments.
1. GEOPHYSICAL FORCING DATA
1.1 Meteorological data
Numerical weather prediction models – examples of specific data providers
The following are examples – listed alphabetically – of WMO centres offering global data that may be accessed directly. The data may also be accessed via the WMO Information System (WIS). In addition, these centres and many other WMO centres offer online regional data sets at higher resolutions.
Deutscher Wetterdienst (DWD) Icosahedral Nonhydrostatic Model (ICON)
Geographical coverage: Global
Resolution of data: 13 km
Forecast data: 7.5 d ahead
Multi-year series available: Availability unknown
Relevant variables: Near-surface wind velocity, near-surface air temperature
Access: Free
Link to data access: https://opendata.dwd.de/
Formats: GRIB2
Download protocols: HTTPS (wget)
Environment and Climate Change Canada (ECCC) Global Deterministic Prediction System (GDPS)
Geographical coverage: Global
Resolution of data: 15 km
Forecast data: 10 d ahead
Multi-year series available: Availability unknown
Relevant variables: Near-surface wind velocity, near-surface air temperature
Access: Free
Link to data access: https://dd.weather.gc.ca/model_gem_global/15km/
Formats: GRIB2
Download protocols: HTTPS (wget), FTP/FTPS, WMS
Japan Meteorological Agency (JMA) High-resolution Global Spectral Model (GSM)
Geographical coverage: Global
Resolution of data: 25 km (0.25° longitude × 0.25° latitude)
Forecast data: 5.5 and 11 d ahead
Multi-year series available: Yes (55 years)
Relevant variables: Near-surface wind velocity, near-surface air temperature
Access: Free with registration
Link to data access: https://www.wis-jma.go.jp/cms/gsm/tutorial.html
Formats: GRIB2
Download protocols: HTTPS (wget)
Météo-France ARPEGE
Geographical coverage: Global, Europe
Resolution of data: Global 0.5° longitude × 0.5° latitude, Europe 0.1° longitude × 0.1° latitude
Forecast data: 5 d ahead
Reanalysis available: Availability unknown
Multi-year series variables: Near-surface wind velocity, near-surface air temperature
Access: Free with registration
Link to data access: https://donneespubliques.meteofrance.fr
Formats: GRIB2
Download protocols: HTTPS (wget)
National Oceanic and Atmospheric Administration (NOAA)/National Centers for Environmental Prediction (NCEP) Global Forecast System (GFS)
Geographical coverage: Global
Resolution of data: 50 km (0.5° longitude × 0.5° latitude)
Forecast data: 8 d ahead
Multi-year series available: Yes (44 years)
Relevant variables: Near-surface wind velocity, near-surface air temperature
Access: Free
Link to data access: https://pae-paha.pacioos.hawaii.edu/thredds/catalog/ncep_global/catalog.html
Formats: netCDF
Download protocols: OPeNDAP, ERDDAP, WMS, WCS, NCSS (subsetting)
United Kingdom of Great Britain and Northern Ireland Met Office Unified Model (UM)
Geographical coverage: Global
Resolution of data: 10 km (0.09° longitude × 0.09° latitude)
Forecast data: 7 d ahead
Multi-year series available: Availability unknown
Relevant variables: Near-surface wind velocity, near-surface air temperature
Access: By subscription after registration; free data up to 1 GB per month
Link to data access: https://metoffice.apiconnect.ibmcloud.com/metoffice/production/
Formats: GRIB2
Download protocols: API to download GRIB2 files
Observational meteorological data – examples of currently available data products
Copernicus Marine Service (CMEMS)
Product ID: WIND_GLO_PHY_L4_NRT_012_004
Observational input: Scatterometers (and European Centre for Medium-Range Weather Forecasts (ECMWF) winds)
Geographic coverage: Global
Spatial resolution: 0.125° × 0.125°
Time resolution: Hourly
Relevant variables: Surface wind components east/north
Access: Free for registered users
Link to data description and access: https://data.marine.copernicus.eu/product/WIND_GLO_PHY_L4_NRT_012_004/description
Formats: netCDF
Download protocols: FTP, OPeNDAP, WMS, MOTU (subsetting)
NOAA National Centers for Environmental Information (NCEI)
Product ID: Blended Six-Hour Seawinds UVComp
Observational input: Scatterometers, radiometers
Geographic coverage: Global
Spatial resolution: 0.25° × 0.25°
Time resolution: 6 h
Relevant variables: Surface wind components east/north
Access: Free
Link to data access: https://coastwatch.noaa.gov/thredds/socd/coastwatch/catalog_ncei_nrt_wind_uvcomp_6hr.html?dataset=CoastWatch/NCEI/Blended/uvcomp/NRTSixHourGlobalAgg/WW00
Formats: netCDF
Download protocols: OPeNDAP, NetcdfSubset, WMS, WCS, ISO, NCML, UDDC
1.2 Oceanographic data
Ocean circulation model data – examples of specific data providers
The oceanographic community has established several portals that offer a range of relevant, freely available, model and observational data at global and regional scales. Examples of global providers include the following.
CMEMS
Geographical coverage: Global plus six European regions (Arctic, North West Shelf, Baltic, Iberia-Biscay-Ireland, Mediterranean, Black Sea). All regions include a three-dimensional (3D) product and a surface product at higher temporal frequency. Depths given are for available output products. All products listed include current velocity components. Consult “Link to data access” below for detailed information.
Resolutions:
- Global 3D – temporal: 6 h; horizontal: 0.083° × 0.083°; vertical levels: 50; levels upper 10 m: 0.5, 1.5, 2.7, 3.8, 5.1, 6.4, 7.9, 9.6
- Global Surface – temporal: 1 h; horizontal: 0.083° × 0.083°; upper level thickness: 1 m
- Arctic 3D – temporal: 24 h; horizontal: 12.5 km × 12.5 km; vertical levels: 12; levels upper 50 m: 5, 30, 50
- Arctic Surface – temporal: 1 h; horizontal: 12.5 km × 12.5 km; upper level depth: 5.0
- NorthWestShelf 3D – temporal: 24 h; horizontal: 0.014° × 0.03°; vertical levels: 33; levels upper 50 m: surface (≤0.5 m), 3, 5, 10, 15, 20, 25, 30, 40, 50
- NorthWestShelf Surface – temporal: 1 h; horizontal: 0.014° × 0.03°; upper level thickness: ≤1 m
- Baltic 3D – temporal: 1 h; horizontal: 0.017° × 0.028°; vertical levels: 55; levels upper 50 m: 0.5, 1.5, 2.6, 3.66, 4.7, 5.8, 7.0, 8.2, 9.5, 10.85, 12.3, 13.9, 15.6, 17.5, 19.7, 22.2, 24.9, 28.2, 31.9, 36.2, 41.1, 46.9, 53.6
- Baltic Surface – temporal: 15 min; horizontal: 0.017° × 0.028°; upper level thickness: 1 m
- Iberia-Biscay-Ireland 3D – temporal: 1 h; horizontal: 0.02778° × 0.02778°; vertical levels: 49; levels upper 50 m: 0.5, 1.5, 2.6, 3.8, 5.1, 6.4, 7.9, 9.6, 11.4, 13.5, 15.8, 18.5, 21.6, 25.2, 29.4, 34.4, 40.3, 47.4, 55.8
- Iberia-Biscay-Ireland Surface – temporal: 15 min; horizontal: 0.02778° × 0.02778°; upper level thickness: 1 m
- Mediterranean 3D – temporal: 1 h; horizontal: 0.0417° × 0.0417°; vertical levels: 141; levels upper 50 m: 1.0, 3.2, 5.5, 7.9, 10.5, 13.3, 16.3, 19.4, 22.7, 26.2, 29.9, 33.8, 37.9, 42.1, 46.7, 51.4
- Mediterranean Surface – temporal: 15 min; horizontal: 0.0417° × 0.0417°; upper level thickness: 2.1 m
- BlackSea 3D – temporal: 1 h; horizontal: 0.025° × 0.025°; vertical levels: 121; levels upper 50 m: 0.5, 1.5, 2.5, 3.5, 4.5, 5.5, 6.5, 7.5, 8.6, 9.6, 10.6, 11.6, 12.7, 13.7, 14.7, 15.8, 16.8, 17.9, 18.9, 20.0, 21.0, 22.1, 23.2, 24.3, 25.4, 26.5, 27.6, 28.7 29.9, 31.0, 32.2, 33.4, 34.6, 35.8, 37.1, 38.3, 39.6, 40.9, 42.3, 43.6, 45.0, 46.5, 47.9, 49.5, 51.0
- BlackSea Surface – temporal: 15 min; horizontal: 0.025° × 0.025°; upper level thickness: 1 m
Forecast data: 10 d ahead
Relevant variables: Current profile, temperature profile, salinity profile, vertical diffusivity profile, mixed layer depth, sea ice concentration, sea ice velocity
Multi-year series available: Yes (25–32 years depending on region, updated annually)
Access: Free for registered users
Link to data access: https://data.marine.copernicus.eu/products
Formats: netCDF
Download protocols: FTP, OPeNDAP, WMS, MOTU (subsetting)
ECCC Global Ice Ocean Prediction System (GIOPS)
Geographical coverage: Global
Resolution: Temporal: 3 h; horizontal: tri-polar ORCA grid with a nominal resolution of 0.25° (12–28 km); vertical levels: 50; levels upper 50 m: 0.0, 0.5, 1.5, 2.6, 3.8, 5.1, 6.4, 7.9, 9.6, 11.4, 13.5, 15.8, 18.5, 21.6, 25.2, 29.5, 34.4, 40.3, 47.4, 55.8
Forecast data: 10 d ahead
Relevant variables: Current profile, temperature profile, salinity profile, sea ice concentration, sea ice velocity
Multi-year series available: Availability unknown
Access: Free
Link to data access: https://dd.weather.gc.ca/model_giops/
Formats: netCDF
Download protocols: HTTPS (wget), FTP/FTPS, WMS
HYCOM.org GOFS 3.1
Geographical coverage: Global
Resolution: Temporal: 3 h; horizontal: 0.08° x 0.04°; vertical levels: 40; levels upper 50 m: 0, 2, 4, 6, 8, 10, 12, 15, 20, 25, 30, 35, 40, 45, 50
Forecast data: 7 d ahead
Relevant variables: Current profile, temperature profile, salinity profile, sea ice concentration, sea ice velocity
Multi-year series available: Yes (22 years)
Access: Free
Link to data access: https://www.hycom.org/dataserver
Formats: netCDF
Download protocols: FTP/FTPS, OPeNDAP, WMS, WCS, NCSS (subsetting)
Further sources of ocean model data may be found in the OceanPredict collaboration, which includes several leading ocean forecasting centres (including some already referred to above).
Observational oceanographic data
Examples of currently available data products from the high-frequency (HF) radar
Coast of European countries
Information source: European Global Ocean Observing System (EuroGOOS) HF Radar Task Team (https://eurogoos.eu/high-frequency-radar-task-team/)
Spatial resolution: Various, depending on location
Time resolution: Various, depending on location
Relevant variables: Surface current components and/or radial velocities, depending on location
Access: Free
Link to data access: https://thredds.hfrnode.eu:8443/thredds/catalog.html
Formats: netCDF
Download protocols: OPeNDAP, DAP4, NetcdfSubset, WMS, WCS, CdmRemote, ISO, NCML, UDDC
Coast of United States of America
Information source: Integrated Ocean Observing System (IOOS; https://hfradar.ioos.us/)
Spatial resolution: 1 km, 2 km, 6 km, depending on location
Time resolution: Hourly, 25 h, monthly, annual means
Relevant variables: Surface current components east/north
Access: Free
Link to data access: https://hfrnet-tds.ucsd.edu/thredds/catalog.html
Formats: netCDF
Download protocols: OPeNDAP, NetcdfSubset, WMS, WCS, ISO, NCML, UDDC
Examples of currently available data products of geostrophic currents from satellite altimetry
CMEMS
Product ID: SEALEVEL_GLO_PHY_L4_NRT_OBSERVATIONS_008_046
Observational input: Altimeter
Geographical coverage: Global
Spatial resolution: 0.25° × 0.25°
Temporal resolution: Daily
Relevant variables: Surface geostrophic current components
Access: Free for registered users
Link to data access: https://data.marine.copernicus.eu/product/SEALEVEL_GLO_PHY_L4_NRT_OBSERVATIONS_008_046/description
Formats: netCDF
Download protocols: FTP, OPeNDAP, WMS, MOTU (subsetting)
Product ID: MULTIOBS_GLO_PHY_L4_NRT_015_003
Geographical coverage: Global
Spatial resolution: 0.25° × 0.25°
Temporal resolution: 6 h, daily, monthly
Relevant variables: Surface geostrophic current components, 15 m modelled Ekman current components
Access: Free for registered users
Link to data access: https://data.marine.copernicus.eu/product/MULTIOBS_GLO_PHY_NRT_015_003/description
Formats: netCDF
Download protocols: FTP, OPeNDAP, WMS, MOTU (subsetting)
Product ID: MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012
Geographical coverage: Global
Spatial resolution: 0.25° × 0.25° x 50 levels
Temporal resolution: Weekly, monthly
Relevant variables: Geostrophic current profile
Access: Free for registered users
Link to data access: https://data.marine.copernicus.eu/product/MULTIOBS_GLO_PHY_TSUV_3D_MYNRT_015_012/description
Formats: netCDF
Download protocols: FTP, OPeNDAP, WMS, MOTU (subsetting)
Examples of currently available data products from the Automatic Identification System (AIS)
At present, current data from regions of heavy ship traffic can be contracted from a single known commercial provider on request. However, CMEMS is evaluating (2024) the incorporation of AIS-derived surface current data into its suite of in situ current products, as a Service Evolution activity.
Examples of currently available data products of tidal constituent
FES2014 provided by Collecte Localisation Satellites (CLS)
Data input: Satellite altimeters, tide gauges
A global data set is available online for the global ocean (1/16°)
Tidal constituents included: 8 primary and 26 additional constituents
Software used for tidal currents: FES2014a (Lyard et al., 2021); FES2022 (Tchilibou et al., 2022)
The constituent data set and other information are available online at https://sirocco.obs-mip.fr/products/tides/global-tidal-atlases/ for FES2014 and at https://www.aviso.altimetry.fr/en/data/products/auxiliary-products/global-tide-fes.html for FES2022.
TPXO provided by Oregon State University (OSU)
Data input: Satellite altimeters, tide gauges
Data sets are available online for the global ocean (1/30°) and for several regional/local domains
Tidal constituents include: 8 primary and up to 11 additional constituents
Software used: OSU Tidal Inversion Software (OTIS; Egbert and Erofeeva, 2002)
Constituent data sets, OTIS and OSU Tidal Prediction Software (OTPS) are available online at https://www.tpxo.net/home. An online calculator is available at https://tpxows.azurewebsites.net/.
1.3 Wave data
Wave model data – examples of specific data providers
The following are examples – listed alphabetically – of centres offering global wave data that may be accessed directly. In addition, many WMO centres offer online global and regional data sets.
CMEMS
Geographical coverage: Global, six European regions
Resolutions: Global 0.083°, regions 1.1–3 km
Forecast data: 10 d ahead
Relevant variables: Significant wave height (total, swell and wind waves), mean wave period (swell, wind waves, spectral peak), Stokes drift velocity components
Multi-year series available: Reanalyses (25–32 years depending on region, updated annually; lower resolution than forecast data)
Access: Free for registered users
Link to data access: https://data.marine.copernicus.eu/products
Download protocols: FTP, OPeNDAP, WMS, MOTU (subsetting)
ECCC Global Deterministic Wave Prediction System (GDWPS)
Geographical coverage: Global
Resolutions: 25 km
Forecast data: 5 d ahead
Relevant variables: Significant wave height (total), mean wave period, peak wave period
Multi-year series available: Availability unknown
Access: Free
Link to data access: https://dd.meteo.gc.ca/model_gdwps/25km/
Download protocols: HTTPS (wget), FTP/FTPS, WMS
JMA Global Wave Model (GWM)
Geographical coverage: Global
Resolutions: 50 km (0.5° longitude x 0.5° latitude)
Forecast data: 5 d ahead
Relevant variables: Significant wave height (total), mean wave period, peak wave period
Multi-year series available: Availability unknown
Access: Free
Link to data access: https://www.wis-jma.go.jp/cms/index.html
Download protocols: HTTPS (wget), WMS
Météo-France Wave Prediction System (WW3)
Geographical coverage: Atlantic Ocean, Mediterranean Sea
Resolutions: 200 m to 5 km
Forecast data: 4 d ahead
Relevant variables: Significant wave height (total), mean wave period, peak wave period
Multi-year series available: Availability unknown
Access: Free
Link to data access: https://donneespubliques.meteofrance.fr/
Download protocols: HTTPS (wget), FTP/FTPS, WMS
NOAA/NCEP WaveWatch III (WW3)
Geographical coverage: Global
Resolution of data: 50 km (0.5° longitude x 0.5° latitude)
Forecast data: 5 d ahead
Relevant variables: Significant wave height, peak wave period
Multi-year series available: Hindcast 1979–2009 (0.5°), 2005–2017 (0.067°–0.167°)
Access: Free
Links to data access
Forecast data: https://pae-paha.pacioos.hawaii.edu/thredds/catalog/ww3_global/catalog.html
Hindcast data: https://polar.ncep.noaa.gov/waves/hindcasts/
Download protocols: Forecast data: OPeNDAP, ERDDAP, WMS, WCS, NCSS (subsetting); hindcast data: FTP
Observational wave data – examples of specific data providers
The following satellite products are provided by CMEMS
Product ID: WAVE_GLO_PHY_SWH_L4_NRT_014_003
Observational input: Altimeter (multiple satellites)
Geographical coverage: Global
Spatial resolution: 2.0° x 2.0°
Temporal resolution: 24 h
Relevant variables: Significant wave height (total)
Access: Free for registered users
Link to data access: https://data.marine.copernicus.eu/product/WAVE_GLO_PHY_SWH_L4_NRT_014_003/description
File formats: netCDF
Download protocols: FTP, OPpeNDAP, WMS, MOTU (subsetting)
Product ID: WAVE_GLO_PHY_SPC_L4_NRT_014_004
Observational input: Synthetic Aperture Radar (Sentinel-1 satellites)
Geographical coverage: Global
Spatial resolution: 1.0° x 1.0°
Temporal resolution: 1 h
Relevant variables: Significant wave height (swell), peak wave period (swell), peak wave direction (swell)
Access: Free for registered users
Link to data description and access: https://data.marine.copernicus.eu/product/WAVE_GLO_PHY_SPC_L4_NRT_014_004/description
File formats: netCDF
Download protocols: FTP, OPeNDAP, WMS, MOTU (subsetting)
2. DETECTION AND MONITORING
2.1 Oil spills
Examples of satellite-based monitoring systems include:
- The CleanSeaNet (CSN) service developed by the European Maritime Safety Agency (EMSA). The system uses Synthetic Aperture Radar satellite images to locate and follow oil pollution, monitor accidental or deliberate pollution and identify polluters. CSN uses images from several satellites to provide near-real-time full-resolution images of up to 1 400 km. Synthetic Aperture Radar satellites can map a body of water based on the amount of disturbance on the surface created by ocean winds. When oil is present, it appears darker than the surrounding area, allowing the satellites to map and locate an accumulation of oil. CSN allows member States access to the images produced by Synthetic Aperture Radar satellites, and if a large-scale pollution event is found, the national operational response mechanism is enacted. The system uses an Alert Matrix based on the likelihood, culprit and impact of the spill to describe the severity of the incident using the colours red, yellow and green.
- The Radarsat Constellation Mission (RCM) operated by the Canadian Space Agency (CSA). The RCM system consists of a fleet of three identical satellites, each equipped with Synthetic Aperture Radar technology. The Synthetic Aperture Radar can provide all-weather, day-and-night imaging capabilities, allowing for continuous monitoring of Canada’s vast maritime regions. The RCM system offers two levels of service for oil spill monitoring. Level 1 service provides basic data products that can be used to detect and locate oil spills. Level 2 service provides more advanced data products, including information on the size, shape and trajectory of the spill. The RCM system is capable of detecting oil spills as small as 100 m2 in size. It can also track the movement of oil spills over time, providing valuable information for response efforts.
2.2 Radioactive materials
The International Atomic Energy Agency (IAEA) Environment Laboratories in Monaco host and maintain the IAEA Marine Radioactivity Information System (MARIS) that allows free access to results of measurements of radioactivity in seawater, biota, sediment and suspended matter. MARIS is compiled from an IAEA in-house database called the Global Marine Radioactivity Database (GLOMARD), which is the primary repository for marine radioactivity measurements curated by the IAEA Environmental Laboratories.
3. OPERATIONAL TRANSPORT AND FATE MODELS
3.1 Oil spills
Multinational efforts
- North West Shelf Operational Oceanography System (NOOS)-Drift: In the North Sea area, NOOS – a regional alliance – is working to develop and employ best practices among the national oil spill forecasting services. As an example, the Swedish oil drift forecasting system Seatrack Web (STW; Ambjörn, 2006) covers the needs of national and international users in the Baltic Sea and a part of the North Sea. It is the official HELCOM drift model/forecasting and hindcasting system that is used for calculating the fate of oil spills. It is available online for national authorities and certain research organizations. A further example is the Oil Spill Evaluation and Response Integrated Tool (OSERIT; Legrand and Dulière, 2014), first developed in Belgium, which is now serving the needs of EMSA-CSN in the North Sea. NOOS-Drift is a transnational multimodel ensemble system that can produce drift forecasts on demand, based on several drift models including OSERIT, OpenDrift and Modèle Océanique de Transport d’hydrocarbures (MOTHY). It enables improving end user trust in drift model results and helps to guide them in their decision-making process, which is a real need expressed by users. NOOS-Drift includes a set of quantified indicators for drift trajectory accuracy, estimated from the spread of the participating drift model forecasts. It helps to discriminate which differences are due to different trajectory models and which are due to different forcing data. It benefits from operational oceanographic forecasts provided by CMEMS. The service domain is the whole European North West Shelf Seas, with a focus on the territorial waters and exclusive economic zones of Belgium, France and Norway.
- Mediterranean Decision Support System for Marine Safety (MEDESS-4MS): In the Mediterranean Sea, the Mediterranean Oceanography Network for Global Ocean Observing System (MONGOOS) operational oceanography community and National Meteorological and Hydrological Services (NMHSs) followed a concept of integration of the existing national meteorological and oceanographic forecasting systems and CMEMS to establish a dedicated online data repository, thereby facilitating access to all these data for their use with well-established oil spill models in the region. A multimodel oil spill prediction service has been set up, known as MEDESS-4MS. MEDESS-4MS (Zodiatis et al., 2016) is also integrated with data from the oil spill monitoring platforms, including the satellites, and offers a range of service scenarios, multimodel data access and interactive capabilities to serve the needs of the Regional Marine Pollution Emergency Response Centre for the Mediterranean Sea (REMPEC), EMSA-CSN and national users such as coast guards. MEDESS-4MS did not lead to an operational system, but served as a precursor for the development of similar systems such as NOOS-Drift.
- Northwest Pacific Action Plan (NOWPAP) Marine Environmental Emergency Preparedness and Response Regional Activity Centre (MERRAC): In the western North Pacific, oil spill responses have been conducted mainly by domestic agencies like the coast guard in many countries. However, the severe spill case of Nakhodka in 1997 raised awareness of the importance of systematic spill prediction and response. The Japan Coast Guard (JCG) and JMA contracted a cooperative framework to enhance the response capacity. JMA developed an oil spill simulation model (JMA, 2022), which also provides spill predictions to other member countries within the WMO framework (see Guide to Marine Emergency Response, Appendix 1). Once an oil spill is reported, JCG provides accident condition data (location, time, oil type and spilled amount and so forth), and JMA produces spill forecasts. The forecasts are delivered to JCG, along with meteorological and oceanographic conditions to support response activities. During a spill incident in 2021, predictions like those shown in the figure were provided to JCG. The Nakhodka case was also a trigger for enhancing an international framework: NOWPAP of the United Nations Environment Programme (UNEP), whose members are China, Japan, the Republic of Korea and the Russian Federation. In 2000, NOWPAP established MERRAC. Its responsibilities include maintaining and updating the contact details for NOWPAP member countries involved in marine pollution prevention and response, and recording spill incidents of oil and hazardous and noxious substances.
Example of an oil spill forecast product produced by JMA and delivered to JCG, which is the responsible response agency. The oil slick is represented by a cloud of particles (blue dots).
Oil spill monitoring and forecasting
- China’s National Marine Environmental Forecasting Center (NMEFC): The Lagrangian oil spill model used by NMEFC currently covers the north-western Pacific Ocean, but the organization is working on expanding it globally. The model is forced with operational meteorological and oceanographic (metocean) fields produced by the Regional Ocean Modelling System (ROMS) and the Weather Research and Forecasting Model (WRF), from global to Chinese waters.
- General NOAA Operational Modeling Environment (GNOME): The GNOME suite is a set of modelling tools for predicting the fate and transport of pollutants (such as oil) spilled in water. These modelling tools are used for NOAA spill response support and are also publicly available for use by the broader academic, response and oil spill planning communities.
The GNOME suite has a number of components available to users, depending on their application:
○ WebGNOME, a web-based application that provides a user-friendly interface for setting up, running and visualizing spill scenarios.
○ PyGNOME, the computational “engine” of GNOME, which is a stand-alone Python package that includes a command line scripting environment.
○ ADIOS Oil Database, a web-based interface for accessing physical and chemical information on a wide variety of petroleum products. Oil records can be downloaded and used in spill modelling scenarios.
○ GOODS, a web-based application to help users access base maps, ocean currents and winds needed as inputs to spill modelling scenarios.
○ TAP, a contingency planning tool that investigates the probabilities that spilled oil will move and spread in particular ways within a particular area, such as a large bay or inlet. - India oil spill prediction model: The Indian National Centre for Ocean Information Services (ESSO-INCOIS) has developed an oil spill trajectory prediction system to provide guidance to the Indian Coast Guard, the regulatory authority, oil spill responders and the coastal community involved in clean-up and control measures during oil spill events. The operational Online Oil Spill Advisory (OOSA) system is a comprehensive system that includes a GNOME-based oil spill trajectory model, which is driven by operational general ocean circulation models and atmospheric models. The resulting forecasted trajectories are made available on a Geographic Information System (GIS). The OOSA system is capable of generating automated advisories for oil spills in the Indian Ocean region between 60–100° E longitude and 0–25° N latitude. Additionally, OOSA can generate offline advisories upon request from neighbouring countries. Although OOSA is still in its initial stages of addressing plastics, chemicals and radionuclides, it can provide drift trajectory patterns without fate. There is also an operational tool for SAR operations called the Search And Rescue Aid Tool (SARAT).
- JMA oil spill prediction model: In January 1997, the wrecking of the Russian tanker Nakhodka caused a serious oil spill, resulting in significant environmental damage along Japan’s western coast. As a response to this incident, the Japanese Government considered countermeasures for large-scale oil spills, and JMA has been operating its oil spill prediction model since October 1999. The model is designed to predict the behaviour of large-scale oil spills in offshore seas. Using accident information from JCG, JMA generates forecasts with a lead time of up to 192 h. The model is applicable to the entire western North Pacific, and the calculation domain is selected from seven settings ranging from 0.8° × 0.8° to 12° × 12° in latitude and longitude, based on the specific incident conditions. The results of oil spill predictions are shared with the Japanese Government and/or JCG, along with various marine meteorological charts.
- Korea Meteorological Administration (KMA) oil spill prediction model: Since 2016, KMA has been operating its oil spill prediction model. The model is designed to predict the behaviour of large-scale oil spills in offshore seas based on the Lagrangian method. Using information from the Korea Coast Guard, KMA generates forecasts with a lead time of up to 87 h. The model is applicable to the entire western North Pacific, and the calculation input data such as current and wind are selected about 500 m × 500 m in latitude and longitude, based on MOHID model output. The results of oil spill predictions are shared with the Government of the Republic of Korea and/or the Korea Coast Guard, along with various marine meteorological charts.
- MEDSLIK-II: This oil spill model code (De Dominicis et al., 2013a, 2013b) is a freely available community model and can be downloaded from http://www.medslik-ii.org. It is designed to be used to predict the transport and weathering of an oil spill, using a Lagrangian representation of the oil slick.
- MOHID: This Lagrangian oil spill model is a component of the MOHID water modelling system developed by the Technical University of Lisbon. It is available on GitHub.
- MOTHY: Météo-France's MOTHY system is utilized for operational purposes to forecast the movement of pollutants or SAR targets on the surface of the ocean. The system integrates local area hydrodynamic coastal ocean modelling at 1/240° resolution and real-time meteorological and oceanic inputs. It consists of four modules designed for predicting the movement of oil slicks or other drifting substances, cargo containers, SAR targets and sargassum. It has a backtracking capacity. The system is accessible round the clock globally for French authorities, foreign authorities within the WMO framework (see Guide to Marine Emergency Response, Appendix 1) or contracting parties. The system is also deployed in several other national meteorological services (Bulgaria, Greece, Morocco and Tunisia).
- OILMAP: This is an oil spill model system suitable for use in oil spill response and contingency planning. Oil spill modelling using OILMAP provides rapid predictions of the movement of spilled oil. A comprehensive 3D model is included that tracks various hydrocarbon components on the water surface, in the water column and in the air. It is sold by RPS Group.
- OILTOX: This is a Lagrangian oil spill model that is adapted to the Black Sea environment. It includes hundreds of oil types that are transported via the Black Sea.
- OpenDrift: The Norwegian Meteorological Institute has developed OpenDrift (https://github.com/opendrift), an open-source, Python-based framework for Lagrangian particle modelling (Dagestad et al., 2018). OpenDrift features several specific modules, including oil drift, stochastic SAR, pelagic egg and a basic module for atmospheric drift. The framework allows for the ingestion of scalar and vectorial forcing fields from various sources, including ocean, atmosphere and wave models, as well as measurements or a priori values for the same variables. The framework also includes a basic backtracking mechanism. OpenDrift is designed for robustness and is used daily for emergency preparedness modelling, such as oil drift, SAR and drifting ships, at the Norwegian Meteorological Institute.
- Oil Spill Contingency and Response (OSCAR): This is a 3D model developed by SINTEF for planning and responding to oil spills. It calculates the fate and effects of surface releases or blowout/buoyant plume of oil or gas, and includes oil-weathering algorithms and exposure models for fish, birds and sea mammals. OSCAR has been used in oil spill risk assessment, response planning and operations, and has been applied in various locations worldwide. It is routinely used in the United Kingdom for operational forecasting of oil spills.
- OSERIT: This is a 24/7 accessible support tool for evaluation of oil spill in the North Sea. It is used by the Royal Belgian Institute of Natural Sciences (RBINS), by coast guard centres and other governmental authorities.
- POSEIDON OSM: This is an oil spill model developed by the Hellenic Centre for Marine Research (HCMR), based on the Parcels model. It is implemented in the Aegean and Ionian Seas.
Specific capabilities to deal with deep-water accidents
- Blowout and Spill Occurrence Model (BLOSOM): This is a modelling suite developed by the National Energy Technology Laboratory in the United States. It is capable of simulating the fate and transport of subsurface oil blowouts and surface spills. The model is flexible and can be used for basic particle tracking or advanced weathering modules and jet/plume modelling. BLOSOM is designed to handle deep-water blowouts, and integrates various oil types from the ADIOS oil library.
- Comprehensive Deepwater Oil and Gas Model (CDOG): This is a 3D model developed to simulate oil and gas releases from deep-water accidents. The model’s primary objective is research, but United States Government agencies and oil companies are now using it for response purposes.
- OILMAPDEEP: This was developed by Applied Science Associates (ASA) and is used to estimate the fate and transport of subsea releases. OILMAPDEEP is also global in capacity and includes the GIS of RPS ASA.
- TAMOC: This is an open-source model developed by Texas A&M that simulates subsea oil spills and blowout plumes. TAMOC is validated via several experimental studies of bubble plumes. The model’s code is available on GitHub.
3.2 Search and rescue
- Search and Rescue Optimal Planning System (SAROPS): This is a comprehensive SAR planning system utilized by the United States Coast Guard in the planning and execution of nearly all SAR cases in and around the United States of America and the Caribbean. SAROPS has three primary components: the Graphical User Interface (GUI), the Environmental Data Server (EDS) and the Simulator (SIM). Using the Commercial Joint Mapping Tool Kit’s (CJMTK) government licensing of the GIS, SAROPS can be used in coastal and oceanic environments. Built into SIM is the ability to access global and regional wind and current data sets.
- Leeway model: Initially described by Allen (1999) and later by Breivik and Allen (2008), the Leeway model was developed by the United States Coast Guard based on empirically determined coefficients. Since its inception, it has been modified and extended by various systems such as OpenDrift in Norway, MOTHY in France, OCEAN-SAR in Italy and OSERIT in Belgium.
- Canadian Search and Rescue Planning (CANSARP): This is a simulation tool that determines the search area and includes a decision support system to assist the Maritime SAR Coordinator in planning a search. CANSARP is available for free download. Currently, the Canadian Coast Guard (CCG) is working on developing a next-generation decision support system (DSS) to replace CANSARP.
- Several national coast guards around the world use commercial software such as SARMAP (RPS Group), SARMaster (Honeywell) or SARIS (BMT): These software tools calculate the probability of containment (POC), the probability of detection (POD) and the probability of success (POS), based on the guidelines outlined in the International Aeronautical and Maritime Search and Rescue Manual. They also include the feeding of forecast wind and current data.
REFERENCES
- Allen, A. A.; Plourde, J. V. Review of Leeway: Field Experiments and Implementation; United States Coast Guard Research and Development Center, Report No. CG-D-08-99, 1999. https://apps.dtic.mil/sti/tr/pdf/ADA366414.pdf.
- Ambjörn, C. Seatrack Web, Forecasts of Oil Spills, a New Version, Proceedings of IEEE United States/European Union Baltic International Symposium, Klaipeda, Lithuania, 2006. https://doi.org/10.1109/BALTIC.2006.7266187.
- Breivik, Ø.; Allen, A. An Operational Search and Rescue Model for the Norwegian Sea and the North Sea. Journal of Marine Systems 2008, 69 (1–2), 99–113. https://doi.org/10.1016/j.jmarsys.2007.02.010.
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- Japan Meteorological Agency (JMA). Ocean Models, 2022. https://www.jma.go.jp/jma/jma-eng/jma-center/nwp/outline2022-nwp/pdf/outline2022_05.pdf.
- Legrand, S.; Dulière, V. OSERIT: A Downstream Service Dedicated to the Belgian Coastguard Agencies. In Sustainable Operational Oceanography, Dahlin, H.; Flemming, N. C.; Petersson, S. E., Eds., Proceedings of the Sixth International Conference on EuroGOOS, 4–6 October 2011, Sopot, Poland; EuroGOOS, 2014.
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- Zodiatis, G.; De Dominicis, M.; Perivoliotis, L. et al. The Mediterranean Decision Support System for Marine Safety Dedicated to Oil Slicks predictions. Deep Sea Research Part II: Topical Studies in Oceanography 2016, 133, 4–20. https://doi.org/10.1016/j.dsr2.2016.07.014.