marine pollution monitoring and prediction

GODAE Final Symposium, 12 – 15 November 2008, Nice, France

Marine Pollution Monitoring and Prediction

Bruce Hackett, met.no

Eric Comerma, Applied Science Assoc.

Pierre Daniel, Météo-France

Hitoshi Ichikawa, Japan Met. Agency


Outline

• What is the marine pollution problem?– Focus → marine oil pollution

• What use are GODAE products?

• Some examples from oil spill forecasting

• Future perspectives

Aim: Demonstrate the use and benefits of using GODAE ocean data


What is the marine pollution problem?

• A wide range of pollutants in the marine environment

• Main impacts are: - harm to life, property and commerce

- environmental degradation

Chocolate mousse à la Prestige – an emulsion

• Marine oil pollution is a good paradigm for pollution monitoring and prediction:– Indisputably human-caused– Catastrophic events (spectacular)– … and long-term dosages (insidious)– Can be ugly, deadly, illegal and costly– Often transnational– Well-established preparedness; national

and international services


What’s the role of GODAE? (1)

• We need monitoring and prediction for: 1. emergency response to spill

events2. impact assessment, both for

specific events and for scenarios

• Both need a good description of the metocean conditions– Weather, sea-state, ocean

circulation– Observations, hindcast, nowcast

and forecastHeavy seas during Statfjord A spill, Dec

2007


What’s the role of GODAE? (2)

GODAE is important since:

• GODAE systems are providers of observations and ocean circulation forecasts.

• GODAE can also provide archival data for past events and statistical studies.


What’s the role of GODAE? (3)The simple view of emergency forecast systems

Drift model

Initial and forcing data

Output data

Userinterface

GODAE!


Emergency response servicesCritical constraints

• Emergency oil spill response services depend on quick and reliable access to drift prognoses – response time <30 min– 24/7/365 availability

• Critical component for drift forecasting is real-time access to accurate prognostic forcing data:– NWP models: wind, air temp – Wave models: Hs, Stokes drift – Ocean models: currents, temp and salinity

• Access & Accuracy: main challenges to operational ocean forecasting!


GODAE dataWhat use are they to oil spill forecasting?

• “Problem”– GODAE provides data at global to basin scales– Oil spill events are typically near-coastal– Oil spill services are national, with local data sources

• Answer: Use GODAE data to help improve the prediction service by – providing boundary conditions for nesting local models– providing for direct forcing (alternatives, backup, ensembles)– extending the spatial and temporal reach of services

Examples follow


• ASA-SA as a commercial middle-user: – providing MetOcean data downstream services– facilitator, aggregating added value into the data

stream, providing dedicated forecasting services– to understand end-client needs, to deal with

constraints and data availability limitations– bridging the gap between global data providers

(GODAE) and local, very specific user needs (harbour, offshore platforms, etc.)

GODAE & oil spill forecasting – South AmericaASA-SA


GODAE & oil spill forecasting – South America ASA-SA

ASA-SA ocean and oil spill forecasting system for

Petrobras, based on nesting in global ocean data products


GODAE & oil spill forecasting – South America ASA-SA Aggregation to cover data requirements

Global ProductGlobal Product Coastal Coastal ProductProduct

Aggregated Aggregated ProductProduct

Regional Regional ProductProduct

Surface RadarSurface RadarSLDMB’sSLDMB’s

Global NCOM and ADCIRC via EDS Aggregation Service

Aggregation of short and long range CODAR


GODAE & oil spill forecasting – South America ASA-SA buoy validation


GODAE and oil spill forecasting – West PacificJMA forecasting service

Information

for Japan Coast Guard - distribution of spilled oil

Information


Surface winddirection / speed

Wave conditionsignificant wave heightpredominant wave period predominant wave direction

Land / Sea distribution

Current & SST

Ocean data assimilation model

(COMPASS-K MOVE)

Transport by wind Stokes driftAdvection by current Diffusion EvaporationEmulsification

Initial step

Results

Data input

Time integral

Numerical weathermodel

Global Spectral Model(GSM)

Numerical wavemodel

Global Wave Model (GWM)Coastal Wave Model (CWM)

Oil Spill Prediction Model

Initial conditiontime / location of a incidentSpilled oil amount / type


Calculation of positions of the pollution source

Since Sep. 2008

Grid resolution : 2 - 30 km Time step : 1 minute Max. calculation time : 192 hour


GODAE and oil spill forecasting – West PacificJMA forecasting service

Information


Information


Surface winddirection / speed

Wave conditionsignificant wave heightpredominant wave period predominant wave direction

Land / Sea distribution

Current & SST

Ocean data assimilation model

(COMPASS-K MOVE)

Transport by wind Stokes driftAdvection by current Diffusion EvaporationEmulsification

Initial step

Results

Data input

Time integral

Numerical weathermodel

Global Spectral Model(GSM)

Numerical wavemodel

Global Wave Model (GWM)Coastal Wave Model (CWM)

Oil Spill Prediction Model



Calculation of positions of the pollution source

Since Sep. 2008

Grid resolution : 2 - 30 km Time step : 1 minute Max. calculation time : 192 hour

MOVE ocean model:– A GODAE

contribution– Development aided

by GODAE collaboration

– Direct forcing and nesting


GODAE and oil spill forecasting – West PacificJMA ocean forecast model (GODAE)

COMPASS-K MOVE

Kuroshio route

Tokai regionTocharian strait


GODAE and oil spill forecasting – West PacificJMA oil drift validation

Standard : drifting buoy for oil spill tracking radius : 20 cm thickness : 5 cm weight : 4 kg material : expanded polyester

1999 Jan.

1999 Nov.

2001 Feb.

2001 Nov.

2002 Feb.


GODAE and oil spill forecasting – West PacificJMA oil drift validation

Case of East China Sea in November, 2001

:

: simulation with COMPASS-K

: simulation with MOVE-WNP

: oil pursuit buoy


MOTHY

Observations

Cedre, MRCC,

PREMAR

Atmospheric models(ALADIN, ARPEGE, IFS)

Tide

Ocean models(MERCATOR, MFS)

ForecastsImages, GIS, Google Earth

Internet, email, fax

Bathymetry

GODAE and oil spill forecasting – EuropeMétéo-France forecasting service

Schematic of Météo-France general framework with access to local and GODAE prognostic ocean data sets.


GODAE and oil spill forecasting – EuropeMeteo-France – Prestige simulations

Prestige case snapshot 2002-12-13 12 UTC. Prestige trajectory = black line MOTHY (wind only) = blue MOTHY+Mercator = greenMOTHY+FOAM = red.

Observed slicks = black triangles Positive impact of adding GODAE current data (Mercator and FOAM) in waters where the large-scale circulation has a significant impact.

However, there are large differences between the current data sets (Mercator and FOAM).

First use of GODAE / Mersea data was most encouraging


GODAE and oil spill forecasting – EuropeMeteo-France, met.no, UCY – Mersea simulations

6 PTR buoys Western Mediterranean sea

3 Argosphere buoys Eastern Mediterranean sea


GODAE and oil spill forecasting – EuropeMeteo-France, met.no – Mersea simulations

Findings:- Often large differences in the predicted current fields- Drifter trajectories are better reproduced in stable and well marked circulation (left)- Large discrepancies between the predicted currents in the open ocean reflects the fact

that the current field is dominated by unstable mesoscale dynamics (right)- The most accurate results are obtained when applying currents from a local, fine-scale

ocean model nested in basin-scale data.


GODAE and oil spill forecasting – EuropeMeteo-France, met.no – Mersea simulations

MFS 1/16th Mercator MED 1/15th

Mercator Global 1/4th All fields are daily means

for 2007-09-24 00 UTC


GODAE & oil spill forecasting – Future perspectivesData access and accuracy

• Access to ocean data– Immensely improved during GODAE lifetime!– Global GODAE models → global coverage for any

oil spill model.– Demonstrated in projects (e.g. Mersea) and by

individual middle users (e.g. ASA) …– … still need to improve standards for access and

products– Any data policy hindrances remaining?


• Accuracy of ocean data– Still the main source of oil spill forecast error.– GODAE assimilation systems continue to improve forecast

accuracy in the blue ocean (e.g., Kuroshio)… – … but still gross errors in some eddy-rich areas.– Need more detailed currents in coastal and shelf seas →

• Higher resolution models

• Nesting is preferable to direct use

• Tides must be included at some stage

• Improved forcing from atmosphere (high-resolution, high freq data)

• Assimilation of current data (HF radar, drifters)

– Need measures of accuracy to propagate into oil spill forecast results!

GODAE & oil spill forecasting – Future perspectivesData access and accuracy


GODAE & oil spill forecasting – Future perspectivesAddressing accuracy

MF: Merc15th

MF: WindOnly

met.no: Nordic4

met.no: Bio4

met.no: Merc15th

met.no: Merc4th

met.no: TOPAZ

MF: Merc15th

MF: WindOnly

met.no: Nordic4

met.no: Bio4

met.no: Merc15th

met.no: Merc4th

met.no: TOPAZ

Using ensembles to address accuracy / confidence issues:• Single-model – perturbations on one of the models (oil drift and/or

forcing) costly!• Multi-model – aggregating several independent oil spill forecasts• Multi-forcing – same oil spill model, different forcing data (enabled by

GODAE!)• A combination of the above• Requires good analysis and/or interpretation methods


End


Comparison between MOVE-WNP and COMPASS-K

IAU (Incremental Analysis Update; Bloom et al. 1996)

Nudging methodscheme of data assimilation

altimeter data of satellitesgrid point data of sea altitudetarget datafor assimilation

3-dimentional variation method(in which the EOF analyses of the vertical profiles of temperature and salinity are employed ; Fujii and Kamachi 2003)

4-dimentional opiticalinterporlation

scheme ofdata analysis

Assimi-lation

system

etc.

introducednot usedmixture layer process

introducednot usedsea ice model

free surfacerigid ridsurface of sea

54 layers (0-5500m)21 layers (0-4500m)vertical resolution

0.1 x 0.1 degree0.25 x 0.25 degreehorizontal resolution

Oceanmodel

MOVE-WNPCOMPASS-Kelementmodel/system

IAU (Incremental Analysis Update; Bloom et al. 1996)

Nudging methodscheme of data assimilation

altimeter data of satellitesgrid point data of sea altitudetarget datafor assimilation

3-dimentional variation method(in which the EOF analyses of the vertical profiles of temperature and salinity are employed ; Fujii and Kamachi 2003)

4-dimentional opiticalinterporlation

scheme ofdata analysis

Assimi-lation

system

etc.

introducednot usedmixture layer process

introducednot usedsea ice model

free surfacerigid ridsurface of sea

54 layers (0-5500m)21 layers (0-4500m)vertical resolution

0.1 x 0.1 degree0.25 x 0.25 degreehorizontal resolution

Oceanmodel

MOVE-WNPCOMPASS-Kelementmodel/system


GODAE & oil spill forecasting – South America ASA Environmental Data System

Environmental

Data Store

Professional Client Thin/Web Client

Internet

Web Services

Web Service XML Request

NetCDF Data

Catalog ServerModelling Engine

• Spatial / Temporal Aggregation

• Modelling Services (Oil, SAR)

• Resources Monitoring

OGC WMS/WxS

EDS

Winds

Currents

Drifters

Weather

Remote Sources

(public/private, e.g. NOAA, Global/Regional OOS)


GODAE and oil spill forecasting – West PacificJMA model drift validation

February 18, 2002February 19, 2002February 20, 2002February 21, 2002February 22, 2002February 23, 2002February 24, 2002February 25, 2002

:

: track of oil pursuit buoy

: simulation of MOVE-WNP

Case of southeast sea of Hokkaido in February 2002

marine pollution monitoring and prediction

Documents

godae ocean data

oil spill forecasting

use godae data

role of godae

global data providers

godae products

godae systems

data stream