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Health Canada Meteorological Course 101 Dorval, Québec, 17-18 October 2011

A Brief Overview of Atmospheric Transport and Dispersion Models in the Environmental Emergency Response Section. Health Canada Meteorological Course 101 Dorval, Québec, 17-18 October 2011 Alain Malo, Nils Ek, René Servranckx, Dov Bensimon, Pierre Bourgouin

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Health Canada Meteorological Course 101 Dorval, Québec, 17-18 October 2011

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  1. A Brief Overview of Atmospheric Transport and Dispersion Models in the Environmental Emergency Response Section Health Canada Meteorological Course 101 Dorval, Québec, 17-18 October 2011 Alain Malo, Nils Ek, René Servranckx, Dov Bensimon, Pierre Bourgouin Environmental Emergency Response Section Canadian Meteorological Centre Meteorological Service of Canada, Environment Canada

  2. Main Operational Model Atmospheric Transport & Dispersion Models (ATDMs) • Simple Trajectory model (backward/forward modes) • 0th Order Lagrangian Particle Dispersion Model (MLDP0) • 1st Order Lagrangian Particle Dispersion Models: • Short range (MLCD) • Short/Medium/Long range (MLDP1) • Urban Lagrangian Stochastic Model (urbanLS) • Inverse Lagrangian Models • Short range (MLCD) • Long range in Global configuration (MLDP0-inverse/MLGI) • Eulerian model (CANERM has been replaced by MLDP0 as the operational ATDM on 9 April 2009 for RSMC and VAAC (nuclear and volcanic ash) emergency response activities under international commitments.

  3. Overview of ATDMs in EER Section

  4. Trajectory model • Simple 3D trajectory calculations • Horizontal and vertical advection only (Runge-Kutta temporal scheme of order 4) • Simple trajectories for a few air parcels released from different vertical levels • No diffusion • No radioactive decay • No deposition • Forward & backward modes • Can give a feeling of the motion of a plume • Fast to run: very quick response • Authors: CMC/EERS • Model applications: • Medium (from 10 to 100 km) & long range applications (>100 km, up ~104 km) • Simulations up to 10 days in forecast mode

  5. 3D Lagrangian particle model Order 0: Random displacements in the vertical Trajectories calculated based on increments in the particle displacements Turbulence effects modelled according to a vertical diffusion coefficient Horizontal diffusion: order 1 (Mesoscale fluctuations) Meteorology: Full 3D fields Off-line model (resolution depends on the driving met model) Sophisticated emission scenario module controlling source through release rate for each radionuclide over time Multiple sources Radioactive decay Dry and wet deposition Gravitational settling and particle size distribution Forward or adjoint (inverse) mode Concentrations better defined near source than for CANERM (Eulerian model) Authors: CMC/EERS Model applications: Medium (from 10 to 100 km) & long range problems (>100 km, up ~104 km) Simulations up to 10 days in forecast mode (up to 30 days in hindcast mode) Complex meteorological conditions Complex topography Volcanic eruptions Nuclear accident (multiple radionuclides) Foot-and-Mouth Disease (FMD) virus Toxic material fire, chemical release Forest fire, sand dust storm MLDP0(Modèle Lagrangien de Dispersion de Particules d’ordre 0)

  6. 3D Lagrangian particle model Order 1: Langevin stochastic equations for velocities based on TKE theory Trajectories calculated according to increments in particle speeds Parameterization of 3D wind fluctuations Meteorology: Assumption: horizontal uniform winds Vertical and Time variability NWP vertical profile, met tower or manual input Integrated 2-layer wind model Precipitation Rate: 2D RADAR fields Mesoscale fluctuations Radioactive decay (only 1 isotope/simulation) Dry and wet deposition Forward or adjoint (inverse) mode Concentrations more accurate near the source than for MLDP0 or CANERM Authors: University of Alberta & CMC/EERS Model applications: Short-range problems (< 10 km) Simulations up to 12 hrs (forecast or hindcasts) Uniform meteorological conditions Flat and uniform topography Nuclear accident Chemical release Toxic material fire MLCD(Modèle Lagrangien à Courte Distance)

  7. 3D Lagrangian particle model Order 1: Langevin stochastic equations for velocities Trajectories calculated according to increments in particle speeds 3D wind fluctuations based on partition of TKE Horizontal diffusion: order 1 (Mesoscale fluctuations) Meteorology: Full 3D fields Off-line model Sophisticated emission scenario module Multiple sources Radioactive decay Dry and wet deposition Forward or adjoint (inverse) mode Concentrations more accurate near the source than for MLDP0 and CANERM Computationally expensive Parallelized model (2 standards): distributed-memory (MPI) shared-memory (OMP) Must run on CMC’s supercomputer Combines MLDP0’s and MLCD’s advantages Authors: University of Alberta & CMC/EERS Model applications: Short, medium and long-range problems Simulations up to 10 days in forecast mode (up to 30 days in hindcast mode) Complex meteorological conditions Complex topography Nuclear accident (multiple radionuclides) Foot-and-Mouth Disease (FMD) virus Toxic material fire, chemical release Forest fire, sand dust storm MLDP1(Modèle Lagrangien de Dispersion de Particules d’ordre 1)

  8. 3D Lagrangian particle model Building effects explicitly modelled: Channelling along streets Flow reversal in the lee of large buildings Stagnation zones Order 1: Langevin stochastic equations for velocities Trajectories calculated according to increments in particle speeds Passive tracer particles No parameterized diffusion No radioactive decay No deposition Multiple sources Input winds from CFD (Computational Fluid Dynamics) model Off-line model Forward mode Runs on Linux architecture Authors: University of Alberta & CMC/EERS Model applications: Urban scale problems in large cities Simulations up to 1 hour forecast/hindcast modes Complex urban winds conditions Complex urban topography (3D buildings) Nuclear accident, dirty bomb Toxic material fire, chemical release urbanLS(Urban Lagrangian Stochastic Model)

  9. 3D Eulerian model Advection-Diffusion Equation (K-Theory) Semi-Lagrangian advection scheme Source Term: horizontal Gaussian forcing function Poor plume definition near the release location due to Gaussian source term Off-line model Radioactive decay Dry and wet deposition Forward mode Authors: CMC/EERS Model applications: Medium (from 10 to 100 km) & long range applications (>100 km, up ~104 km) Simulations up to 10 days in forecast mode Nuclear explosion (multiple radionuclides) Volcanic eruption Toxic material fire Forest fire Sand dust storm Chemical release CANERM(CANadian Emergency Response Model)

  10. Worldwide Operational ATDMs

  11. Other Worldwide Ops/R&D ATDMs

  12. Other Worldwide Ops/R&D ATDMs

  13. Other Worldwide Ops/R&D ATDMs

  14. ATDMs Acronyms

  15. Organization Acronyms

  16. Organization Acronyms

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