WORLD METEOROLOGICAL ORGANIZATION
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INTERGOVERNMENTAL OCEANOGRAPHIC
COMMISSION (OF UNESCO)
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JOINT WMO/IOC TECHNICAL COMMISSION FOR
OCEANOGRAPHY AND MARINE METEOROLOGY (JCOMM)
EXPERT TEAM ON MARINE ACCIDENT
EMERGENCY SUPPORT
ETMAES-I/Doc. 3.3
(21.XII.2006)
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ITEM 3.3
FIRST SESSION
ANGRA DOS REIS, BRAZIL, 29 TO 31 JANUARY 2007
Original: ENGLISH
REPORT OF THE CURRENT STATUS AND POTENTIAL FOR USE OF THE
OPERATIONAL OCEAN FORECASTING SYSTEMS IN MARITIME ACCIDENT AND
EMERGENCY SUPPORT (MAES) APPLICATIONS
(Submitted by Dr Adrian Hines, Rapporteur on Operational Ocean Forecasting Systems)
Summary and Purpose of Document
This document contains the report of the Rapporteur on Operational Ocean
Forecasting Systems (OFS) that aims to describe the current status and potential
for use of the operational ocean forecasting systems in Maritime Accident and
Emergency Support (MAES) applications.
ACTION PROPOSED
The Expert Team on Marine Accident Emergency Support (ETMAES) is invited to note
and comment on the information provided as appropriate, and generally to take it into account
when discussing relevant agenda items.
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ETMAES-I/Doc. 3.3, p. 2
DISCUSSION
1.
Introduction
1.1
Recent progress with development of operational ocean forecasting systems has
produced systems with suitable levels of maturity for consideration for use in Maritime Accident
and Emergency Support (MAES) scenarios. Whilst at present these systems are not widely
used on a routine basis, demonstrations of capability have been undertaken. These
demonstrations have highlighted both the potential and current limitations of the systems for
these applications.
1.2
Potential for use of the operational ocean forecasting systems falls within three main
application areas: search and rescue, counter-pollution and nuisance and harmful algae blooms.
The requirements for inputs from the ocean forecasting systems for the first two of these are
very closely related.
1.3
This document aims to describe the current status and potential for use of the operational
ocean forecasting systems in Maritime Accident and Emergency Support (MAES) applications.
2.
Application to Search and Rescue and Counter-Pollution
2.1
Systems for use in search and rescue and for response to incidents of pollution typically
require inputs of environmental information such as wind speed and direction, current speed and
direction, and in a polar environment, sea-ice cover. In addition, variables such as temperature
and salinity (or equivalently density) and sea state can have an impact on survivability of a
casualty, and on the sinking, weathering and dispersion of pollutants. In general, whilst systems
may have access to real-time meteorological information, oceanographic data is usually
specified as a single, constant climatological value, for example a prevailing current direction
and climatological current speed, or values from a tidal database if in tidal waters.
2.2
Many of the systems in use, however, have the capability to ingest and exploit gridded
model data, typically supplied in a standard format (e.g., GRIB). This opens up the possibility of
use of outputs from the latest generation of operational ocean forecasting systems.
2.3
Forecasting systems for the ocean interior are typically configured to provide eddypermitting or eddy-resolving resolution for the major ocean basins, with higher resolution models
available for coastal regions of particular interest. Models are configured to include the
representation of tides in strongly tidal regions, and sea-ice at high latitudes. The eddy resolving
models are dependent either upon the assimilation of data, in particular satellite altimeter sea
surface height data, or the realistic simulation of tides and tidal mixing to accurately represent
the mesoscale fronts and eddies that characterize the ocean circulation. In addition,
specification of an accurate bathymetry, and accurate surface wind stresses are essential to
ensure realistic representation of the ocean currents.
2.4
Products delivered by the systems include 3D gridded fields of ocean state variables,
including currents, temperature and salinity on a range of vertical levels and sea-ice
concentration. Fields are typically output at 6-, 12- or 24-hour intervals for the open ocean, as
either instantaneous or time mean fields, or alternatively as hourly currents in tidal waters. Some
systems are run daily, taking advantage of meteorological infrastructure to provide full
operational support, whilst others are run less frequently on a pre-operational basis. The MAES
applications clearly require fail-safe systems and operational, robust delivery mechanisms to
deliver the data to the applications. Such capability is potentially available from the ocean
forecasting systems that are currently run operationally, whilst many of the systems that are
currently run pre-operationally have plans to develop full operational capability.
ETMAES-I/Doc. 3.3, p. 3
2.5
Demonstrations of oil spill drift predictions using case studies have highlighted some of
the challenges in using the operational ocean forecast system outputs within the MAES
applications. Comparisons of predictions from a number of systems identified significant
differences in the predicted direction of drift (Figure 1), and highlighted the need for further
investigation of the optimal strategy for interfacing the MAES applications to the operational
ocean forecasting systems. Particular issues arising are: the optimality of the system output
frequency, the use of mean fields compared to instantaneous fields, the resolution and
frequency of the surface wind stresses used, the physical formulation of the ocean model, and
the horizontal and vertical resolution of the ocean model. Despite these discrepancies, the
ocean forecasting systems showed potential to improve the outcome of the drift predictions over
and above that provided by the use of climatological data.
Figure 1 – Comparison of drift simulations undertaken by Météo-France. Simulation using the Mercator-Ocean
Psy1v2 surface sea current (upper left panel), HYCOM mixed layer sea current (upper right panel), FOAM 5 m
sea current (lower left panel) and TOPAZ 5 m sea current (lower right panel).
Figure 2 – Comparison of drift predictions in the Irish Sea undertaken by the UK Met Office. Using 12km
resolution currents and 60km resolution winds (left), 12km currents and 12km winds (centre), and 1 nautical mile
currents and 12km winds (right).
ETMAES-I/Doc. 3.3, p. 4
2.6
Separate studies exploring the sensitivity of surface drift predictions in SAR scenarios
have highlighted the impact of high resolution surface forcing, particularly when used in
conjunction with a high resolution ocean model (Figure 2).
2.7
These studies have identified the potential for the operational ocean forecasting systems
to provide enhanced predictive capability for search and rescue and counter-pollution
applications. However, to harness these capabilities to full advantage it is necessary to continue
to develop the systems, and to begin to gather practical experience in their application to
develop a more thorough understanding of their abilities and limitations.
2.8
Ultimately, it may prove advantageous to run predictions of drift for MAES applications inline with the underlying ocean forecasting system runs. This is likely to provide the most
accurate simulation of the drift as currents used within the prediction would be updated on every
model time-step, ensuring in particular that extremes within the currents are not lost due to
averaging. However, this type of system would require some development, and would most
notably require the ocean forecast systems to be run on demand following an incident. This is
unlikely to be feasible in the foreseeable future.
2.10 Operational surface wave forecasting systems form a separate class of operational
models that are more mature and more widely used for a range of applications. Such models
are developed and run in most operational NWP agencies, and provide robust forecasts of
surface wave conditions. Due to strong dependencies on surface stresses from the NWP model
systems, the surface wave forecasts are typically run within the NWP forecast cycle, producing
hourly outputs at moderate resolution for ocean basins, and high resolution for regional and
coastal configurations.
2.11 Despite the relative maturity of the surface wave forecasting systems and their existing
application by marine forecasting centres, they are not currently widely used by the community
engaged in MAES. The uncertainty of such forecasts is well characterized, and the strengths
and limitations are well understood by marine forecasters. In consequence, their use in MAES
scenarios should be both advantageous and relatively straightforward.
2.12 The potential to exploit the operational ocean forecasting systems for search and rescue
and counter pollution goes beyond the provision of real-time forecast data into the systems
employed for the immediate response. The need for a response over longer timescales has
been illustrated by recent SAR examples where searches have continued for periods of up to
one month after an incident. These searches have made ad hoc use of archives of model
estimates to provide time history of the evolution of the ocean state for use in simulation of the
drift. The operational ocean forecast systems with their associated archives provide a means to
rapidly access historical information in such cases.
2.13 A further potential application of the operational ocean forecast systems and associated
data archives is in the area of attribution of the source of a particular pollutant or drifting object.
Sophisticated systems have been developed for use in attribution problems in the atmosphere,
and allow the evolution of a plume or the track of an object to be projected back in time to
determine the likely source. Such systems could be adapted or developed for use in
oceanographic attribution problems.
3.
Application to Nuisance and Harmful Algae Blooms
3.1
The application of operational ocean forecasting systems to the prediction of nuisance
and harmful algae blooms is an area of emerging capability which has received particular
attention in Europe, with several potentially useful contributions provided by the forecasting
systems.
ETMAES-I/Doc. 3.3, p. 5
3.2
On the most simple level, the physical fields provided by the forecast system can be used
with schemes for detection of blooms based on satellite data to determine the likely spread due
to advection, and in particular the likelihood of landfall of a particular bloom event. In this regard,
the requirements and application are analogous to that of the counter-pollution applications.
3.3
At a more sophisticated level, the current generation of marine ecosystem models are
able to simulate the evolution of numerous classes of plankton, and can provide indicators of
conditions that are conducive to algae blooms. Predictions of levels of nutrient and dissolved
oxygen are among the most reliable outputs of the ecosystem modeling systems, and can
provide evidence of environmental conditions in which blooms could be supported.
3.4
Whilst it is not currently possible to predict with confidence the presence or otherwise of a
bloom at a particular location, or whether a particular bloom is likely to be harmful, indications of
prevailing conditions that are likely to be suitable for a bloom to occur can be used to direct
further observational monitoring. An example of a likelihood product provided in this context is
shown in Figure 3. The application of these systems therefore lies in the area of risk
management, rather than in direct response. Nonetheless, this should be key information to
ensure a state of readiness should a bloom ensue.
Figure 3 – Example of a warning plot to indicate the likelihood of a harmful algae bloom in UK waters. Red is
high likelihood, amber is medium, green is low.
3.5
Development of suitably robust indicators requires good understanding and skilled
interpretation of the model predictions. Such indicators are now being trialed by various groups
for particular areas of the coastal ocean.
4.
Summary
4.1
There are clear potential benefits to the use of operational ocean forecasting system
output in response to MAES incidents, subject to further work to gain experience and to clearly
understand the strengths and limitations of the systems in this context. Such work is feasible
with the current generation of MAES response systems.
4.2
There are three main areas of application: search and rescue, counter-pollution, and
nuisance and harmful algae blooms. For the first two applications, the primary contribution of
the forecasting systems is the provision of gridded, time-evolving estimates of the ocean
currents, accompanied with secondary variables such as temperature, salinity and sea-ice
ETMAES-I/Doc. 3.3, p. 6
concentration. Surface wave forecasting systems are sufficiently mature to allow ready
application within the response systems; application of forecasts of the ocean interior requires
further exploration. For the third application, the physical variables could be applied for the most
basic predictions of advection, whilst ecosystem models can provide indicators of the suitability
of conditions for the development of blooms.
4.3
Successful application of the outputs of these systems to MAES response requires the
MAES community and the operational ocean forecasting community to collaborate to further
develop demonstration cases that allow experience to be gained, the suitability of models for this
purpose to be improved, and confidence to be built between the two communities. Work will
also be required to develop suitably robust interfaces between the operational ocean forecasting
systems and the MAES applications.
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