Meteorologisk institutt met.no LEO Long-term effects of oil accidents on the pelagic ecosystem of the Norwegian and Barents Seas Yvonne Gusdal.

Slides:



Advertisements
Similar presentations
Meteorologisk Institutt met.no Ocean Surface Warming by Polar lows - Observational Evidence from Microwave Data Øyvind Saetra, Torsten Linders and Steinar.
Advertisements

Meteorologisk Institutt met.no OPNet, Oslo, May 2011 Do we need fine scale ocean prediction ?!... and if so, do we have the right tools ? Lars-Anders Breivik.
Seasonal and Interannual Variability of Peruvian anchovy Population Dynamics --progress report-- Yi Xu and Fei Chai June 2007.
Meteorologisk institutt met.no High waves in the North Sea Nov 2009 Eumetcal NWP course, Dec 2009 Lars Hole.
The 3rd International Workshop on Next Generation Climate Models for Advanced High Performance Computing Facilities Tokyo, Japan, March , 2001 Performance.
NEMO Modelling NSERC – CCAR Projects VITALS Geotraces
Forecasting Polar Lows Gunnar Noer The Norwegian Meteorological Institute in Tromsø.
The Use of High Resolution Mesoscale Model Fields with the CALPUFF Dispersion Modelling System in Prince George BC Bryan McEwen Master’s project
WP12. Hindcast and scenario studies on coastal-shelf climate and ecosystem variability and change Why? (in addition to the call text) Need to relate “today’s”
Title EMEP Unified model Importance of observations for model evaluation Svetlana Tsyro MSC-W / EMEP TFMM workshop, Lillestrøm, 19 October 2010.
Climate modeling Current state of climate knowledge – What does the historical data (temperature, CO 2, etc) tell us – What are trends in the current observational.
Modeling Larval Connectivity for the SoCal Bight Satoshi Mitarai, James Watson & David Siegel Institute for Computational Earth System Science University.
Ocean surface currents and the Craig-Banner boundary condition Charles Tang Bedford Institute of Oceanography Dartmouth, Nova Scotia, Canada POM for the.
Meteorologisk Institutt met.no OPNet, Geilo May 27, 2009LPR 1 The IAOOS Seaglider Project A few notes for the OPNet meeting, May 27-28, 2009 prepared by.
2005 ROMS Users Meeting Monday, October 24, 2005 Coupled sea-ice/ocean numerical simulations of the Bering Sea for the period 1996-present Enrique Curchitser.
Flow, Fish & Fishing A Biocomplexity Project
28 August 2006Steinhausen meeting Hamburg On the integration of weather and climate prediction Lennart Bengtsson.
1 1 NORWECOM in ROMS Morten D. Skogen
Johan Hjort Symposium, Bergen, NO7 Oct Do eggs collected in surveys accurately reflect adult fecundities? Hannes Höffle 1, Frode B. Vikebø 1, Olav.
The SouthEast Coastal Ocean Observing SECOORA Meeting Regional Association (SECOORA) June 11-12, Modeling and Analysis Subsystem {SWG3.3 Chair,
EGU 2012, Kristine S. Madsen, High resolution modelling of the decreasing Arctic sea ice Kristine S. Madsen, T.A.S. Rasmussen, J. Blüthgen and.
Satellite Data Assimilation into a Suspended Particulate Matter Transport Model.
“IDEALIZED” WEST COAST SIMULATIONS Numerical domain Boundary conditions Forcings Wind stress: modeled as a Gaussian random process - Statistics (i.e.,
Istanbul 5 th March 2010 Efficient downscaling to coastal sea using the unstructured finite volume model MIKE 3 – applications in the Ligurian Sea and.
DMI forecasting system for Baltic-North Sea (DMI BSHcmod), and also for Greenland, NW Shelf (Hycom) Jens Murawski (DMI)
The Influence of Diel Vertical Migration on Krill Recruitment to Monterey Bay Sarah Carr Summer Internship Project Monterey Bay Aquarium Research Institute.
Climate Forecasting Unit Arctic Sea Ice Predictability and Prediction on Seasonal-to- Decadal Timescale Virginie Guemas, Edward Blanchard-Wrigglesworth,
Ocean and sea-ice data assimilation and forecasting in the TOPAZ system L. Bertino, K.A. Lisæter, I. Kegouche, S. Sandven NERSC, Bergen, Norway Arctic.
Meteorologisk Institutt met.no Operational ocean forecasting in the Arctic (met.no) Øyvind Saetra Norwegian Meteorological Institute Presented at the ArcticGOOS.
1 1 Jon Albretsen, Anne D. Sandvik and Lars Asplin NorKyst-800: A high-resolution coastal ocean circulation model for Norway St Augustine, Florida, 7-9.
ECOOP annual meeting February 2008 Athens Ole K. Leth Danish Meteorological Institute (DMI) Contribution to WP 4 (13 February 2008) – Modelling and.
Meteorologisk Institutt met.no Operational atmosphere models at met.no Status and future directions Jon Albretsen, Jørn Kristiansen and Morten Køltzow.
Modeling the upper ocean response to Hurricane Igor Zhimin Ma 1, Guoqi Han 2, Brad deYoung 1 1 Memorial University 2 Fisheries and Oceans Canada.
Arctic Operational Oceanography at IMR Einar Svendsen Arctic GOOS planning meeting, September 2006 at NERSC, Bergen.
Status and plans for assimilation of satellite data in coupled ocean-ice models Jon Albretsen and Lars-Anders Breivik.
Validation of decadal simulations of mesoscale structures in the North Sea and Skagerrak Jon Albretsen and Lars Petter Røed.
Transport in Aquatic Ecosystems Horizontal Inflows - Advection Turbulence – critical for vertical fluxes.
1.Introduction Prediction of sea-ice is not only important for shipping but also for weather as it can have a significant climatic impact. Sea-ice predictions.
An air quality information system for cities with complex terrain based on high resolution NWP Viel Ødegaard, r&d department.
Ocean modelling activities in Japan (some of activities in China and Korea are included in the report) report to the CLIVAR Working Group for Ocean Model.
Synthetic Float Analysis in HYCOM Synthetic floats were released in an ocean model to study how the upper-limb (northward return flow) of the Atlantic.
1) What is the variability in eddy currents and the resulting impact on global climate and weather? Resolving meso-scale and sub- meso-scale ocean dynamics.
Analysis of four decadal simulations of the Skagerrak mesoscale circulation using two ocean models Lars Petter Røed 1 and Jon Albretsen 2 Presented at.
Over the northern West Florida Shelf several reef fish species (with gag grouper being a key species) spawn near the outer shelf edge in winter and early.
Provided by Eric P. Chassignet, COAPS, Florida State University HYCOM High Resolution Modeling.
Sea ice modeling at met.no Keguang Wang Norwegian Meteorological Institute.
AOMIP status Experiments 1. Season Cycle 2. Coordinated - Spinup Coordinated - Analysis Coordinated 100-Year Run.
Operational fish larval drift modelling Bjørn Ådlandsvik og Frode Vikebø Institute of Marine Research Opnet meeting, Geilo, May 2008.
NWP models. Strengths and weaknesses. Morten Køltzow, met.no NOMEK
Contributions from: Norwegian Meteorological Institute(met.no) Norwegian Meteorological Institute(met.no) Geophysical Institute, University of Bergen(GfI-UiB)
Regional Advanced School on Physical and Mathematical Tools for the study of Marine Processes of Coastal Areas Physical and Biogeochemical Coupled Modelling.
Visualization of High Resolution Ocean Model Fields Peter Braccio (MBARI/NPS) Julie McClean (NPS) Joint NPS/NAVOCEANO Scientific Visualization Workshop.
Norwegian Meteorological Institute met.no Are North Atlantic SST anomalies significant for the Nordic Seas SSTs? Arne Melsom Norwegian Meteorological Institute,
AO-FVCOM Development: A System Nested with Global Ocean Models Changsheng Chen University of Massachusetts School of Marine Science, USA
HIRLAM coupled to the ocean wave model WAM. Verification and improvements in forecast skill. Morten Ødegaard Køltzow, Øyvind Sætra and Ana Carrasco. The.
THE BC SHELF ROMS MODEL THE BC SHELF ROMS MODEL Diane Masson, Isaak Fain, Mike Foreman Institute of Ocean Sciences Fisheries and Oceans, Canada The Canadian.
Impact of sea ice dynamics on the Arctic climate variability – a model study H.E. Markus Meier, Sebastian Mårtensson and Per Pemberton Swedish.
Hindcasted wave dynamic during the passage of typhoons
Anton Eliassen, Lars Petter Røed and Øyvind Sætra
Forecasting Drifting Objects
October 23-26, 2012: AOMIP/FAMOS meetings
COSA Committee Meeting
WaveFlow KO Øyvind Breivik (MET Norway), Joanna Staneva (HZG), Jean Bidlot (ECMWF) and George Nurser (NOC)
Models of atmospheric chemistry
하구및 연안생태Coastal management
Kai Christensen (met. no), Gøran Brostrøm (met
하구및 연안생태Coastal management
하구및 연안생태Coastal management
하구및 연안생태Coastal management
Title Effect of horizontal resolution on PM calculations:
Presentation transcript:

Meteorologisk institutt met.no LEO Long-term effects of oil accidents on the pelagic ecosystem of the Norwegian and Barents Seas Yvonne Gusdal

Meteorologisk institutt met.no Future oil production accident can be very harmful on the fish stocks –Barents Sea Cod –egg / larvae (passive particles) Egg, larvae and oil trajectories can be simulated by using an advection model forced by currents –Egg an larvae drift is computed based on a semi-Lagrange advection model (Arne Melsom). –Oil drift is simulated based on the oil drift model at the Meteorological Institute

Meteorologisk institutt met.no The impact of the oil accident on the fish eggs/ fish larvae are dependent on: –Sea conditions –Spawning location –Spawning period –Oil spill location/ spill period

Meteorologisk institutt met.no LEO - area

Meteorologisk institutt met.no Sea conditions Currents and hydrography are obtained from a coupled model system consisting of the ocean model MI-POM and the ice model MI-IM. –Area: The Barents Sea and the Norwegian Sea –Simulation period: –Resolution: 4km –Interpolated to a mesh size of 8km

Meteorologisk institutt met.no To provide the best possible description of drift pathways of oil and fish eggs, we have to include the non-deterministic variability in the ocean A ten-member ocean circulation ensemble has been constructed – Each ensemble only differ in the atmospheric forcing Eddy permitting model –However, finer scale processes are not resolved

Meteorologisk institutt met.no Gaussian noise is added to the model results with a velocity: Have only been used in the semi-Lagrange advection model for the egg and larvae drift.

Meteorologisk institutt met.no Spawning period: Cod eggs 1. April 15. April 15. March Particle release of 5 days The particles are advected until September 1th Release depth: 10m and 20m

Meteorologisk institutt met.no Spawning sites: Cod eggs nord yttersida vestfjorden

Meteorologisk institutt met.no

Particle release: larvae June - September Depth: 20m and 30m

Meteorologisk institutt met.no OIL - drift For the oil release, the operational Oil Drift Model at the Norwegian Meteorological Institute is applied. The oil drift is computed on the basis of currents from the ten ensemble members, supplemented by wave induced Stokes drift –Temperature, salinity, significant wave height, wave period and wind are also included –The wind is obtained from HIRLAM, while the operational wave model WAM supplies the oil model with significant wave height, mean wave period and stokes drift.

Meteorologisk institutt met.no OIL - concentration Oil chemestry - toxic –Not included Vertical mixing –Included Toxic – oil concentration –Adding up all submerged oil particles over a volume of 8km x 8km x 10m –Three layers: 0m-10m, 10m – 20m and 20m – 30m.

Meteorologisk institutt met.no OIL drift

Meteorologisk institutt met.no Takk for meg!