Met Office Science Review Meetings 2013
MOSAC 18.15
Atmospheric Dispersion & Air Quality Matthew Hort
Volcanic and Radiological Dispersion
(Manager + 6)
Chemical and Biological Dispersion
(Manager + 6)
Dispersion Processes and
Parameterisations
(Fellow + 4)
Air Quality and Composition
(Manager + 4)
ADAQ Met Office
Chief Scientist
SCIENCE PARTNERSHIPS
Understanding Climate Change
Climate Monitoring & Attribution
Monthly to Decadal Variability & Prediction
Earth System Science & Mitigation Studies
Met Office Hadley Centre CLIMATE SCIENCE
Oceans, Cryosphere & Dangerous Climate Change
Climate Impacts & Adaptation Studies
FOUNDATION SCIENCE
Observational-Based Research
Atmospheric Processes & Parametrizations
Global UM Development & Evaluation
Dynamics Research
APPLIED SCIENCE (NEW)
Applied Climate Science
Applied Weather Science
Scientific Consulting
International business development
Government business ESSP etc...
Operational Weather Forecasting & IT
Satellite Applications
Data Assimilation & Ensembles
Ocean Forecasting
Atmospheric Dispersion and Air Quality
WEATHER SCIENCE
Biological
Volcanic
Chemicals Particulate
Radiological
Air Quality
Health Impacts
Environmental
Impacts
Weather Feedbacks
Atmospheric Process
Chemical Processes
Emissions
ADAQ
• Science
• Response
• Policy support and planning
• Risk assessment
• Consultancy
• Collaboration
ADAQ Drivers
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VAAC’s
RSMC’s PURE
PWS
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NAME Numerical Atmospheric-dispersion
Modelling Environment
AQUM Air Quality in the Unified Model
Recent R&D Highlights NAME
• Urban parameterisation
• Inversion for emergency
response
• Wet deposition updated
• Fukushima
• WHO, UNSCEAR, WMO-TT
• Biological contaminants
Satellite Retrieval
a priori
Inversion solution
Fukushima Cs137 Deposition
Modelled
Observed
Recent R&D Highlights NAME
• Volcanic SO2 modelling
• Singapore – ‘Haze’ forecast
• Operational systems
• VAAC and EMARC systems re-engineered
• Buoyant plume rise
• Consortia
• VANAHEIM, FUTUREVOLC,
RACER, CREDIBLE
© Crown copyright Met Office
Singapore
Recent R&D Highlights AQUM
• Key model paper (Savage et al. 2013)
• Defra model inter-comparison
“AQUM performs best for forecasting
the Daily Air Quality Index”
• AQMEII-2 international model
inter-comparison.
© Crown copyright Met Office
Recent R&D Highlights AQUM
• Health Air
• Aim: Develop a rigorous statistical
framework for estimating the long-term
health effects of air pollution
• Regional Climate Model AQUM
• Some evaluation of complexity of
chemistry schemes/emissions
• Testing @ 4 km
• Still much to be done!
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4 km 12 km
Strategy
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Under Construction
ADAQ - Goals
• Deliver world leading probabilistic impact forecasts (Dispersion and AQ) at scales from 10's of metres to global out to 5 days
• Incorporation of relevant chemical, biological, radiological and volcanological processes
• Contribute to improved UK weather forecasts, especially visibility, through improved representation of atmospheric composition.
• Integrated multi-agency/multi-disciplinary collaborative science and services across all areas
• Deliver growth
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Deliver world leading probabilistic impact forecasts (Dispersion and AQ) at scales from 10's of metres to global out to 5 days.
• Uncertainty – quantification and representation
• Inversion and data assimilation (+ MACC)
• Higher resolution
• 4km (AQ: 2015) ~ 1 km (AQ: ~2018)
• Urban
• Evaluate NWP links and coupling
• Optimal temporal/spatial resolutions
• Coupled Lagrangian-Eulerian
• Weather feedbacks and investigation
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GLA
0 0.2 0.4 0.6 0.8 1 1.2
x (m)
0
0.2
0.4
0.6
0.8
1
y (
m)
0.0 0.2 0.4 0.6 0.8 1.0 1.2
x (m)
0.000
0.001
0.002
0.003
0.004
0.007
0.010
0.016
0.024
0.036
0.055
0.084
0.127
0.194
0.296
C
(a) (b)Leuzzi et al 2012
Incorporation of relevant chemical, biological, radiological and volcanological processes
• Application specific capability is key:
• meteorological dependencies, radiation dose, exotic reactions, etc
• UKCA-GLOMAP-mode
• Climate version – currently expected Q2 FY14/15
• AQUM operational adoption Q2 FY15/16
• Reduced complexity gas phase and aerosol chemistry
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Routine Verification
Midge forecast
Integrated multi-agency/multi-disciplinary collaborative science and services across all areas
• Increased model linkages/coupling
• Emissions
• Health, built and natural environment impacts
• Greater links to academic community
• BADC – JASMIN capability
• Joint projects
• Further develop agency partnerships
• BOM, MSS, NIWA, IMO, PHE, etc
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Challenges
• Diversity
• Expertise thinly spread, single points of failure,
conflicting/rapidly changing external priorities
• Dependencies
• UKCA, UM
• Resource
• Within team and more broadly
• Code management/development
• Code optimisation, integration, coordination
• Operational pull through
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Questions?
Thank you !