Improving the scalability of an emergency response model

The eruption of Eyjafjallajökull in Iceland in April 2010 led to disruption of air traffic around Europe. The Met Office’s NAME model was used to forecast the spread of the plume of ash in the atmosphere.

Image:© iStock.com/JochenScheffl

The UK Met Office’s NAME model can simulate the progress of billions of particles through the global atmosphere, but requires major computing resources to do so. Thanks to work by EPCC, NAME can now run on large parallel systems and promises more accurate forecasts of hazards.

Early on 26th April 1986, Reactor Number 4 at Chernobyl – in what is now Ukraine – suffered a catastrophic failure, causing the release of a large radioactive plume into the atmosphere. Weather conditions at the time caused the contents of the plume to be swept over north-western USSR, and towards Scandinavia and other parts of northern Europe.

This resulted in widespread public health concerns, particularly in upland areas where high rainfall led to significant accumulation of radioactive isotopes such as iodine and caesium on farmland and hence in grazing animals.

One further result of the Chernobyl disaster was the development of what was then referred to as the “Nuclear Accident Model” at the Met Office. Originally intended to simulate the dispersion of radioactive species, interests have expanded to include routine air quality forecasting, and predicting the spread of pollutants, airborne viruses and volcanic ash. Notable occasions when the model has been brought into operational use include the outbreak of foot-and-mouth disease in the UK in 2001, the eruption of Eyjafjallajökull and the consequent disruption to commercial air traffic in April 2010, and during the Fukushima nuclear power station disaster following the tsunami in Japan in 2011.

This widening of the scope of interest has meant the model has been renamed Numerical Atmospheric dispersion Modelling Environment (NAME) [1] .

NAME is a “Lagrangian” model which represents atmospheric dispersion by tracking simulated ‘particles’. Movement through the atmosphere is typically driven by numerical weather prediction data (either historical data or operational forecast) while particles also undergo a random motion to represent small-scale turbulence which is not resolved.

Particles are generated by a specified source or set of sources which may be natural (eg a volcano or a fire) or man-made (eg a factory or other known source of pollution). Particles may be removed from the atmosphere by a number of different processes such as fall-out owing to gravity and impact with the ground, and ‘wash-out’ by rain.

The main computational cost in NAME is therefore representing a large number of simulated particles which carry a significant payload of information (position, velocity, chemical content, and so on). To move forward in time, the properties of each particle must be updated using the relevant dynamics, chemical rate equations, radioactive decay laws and so on. As the statistical accuracy of the results of any given simulation depend upon having a large enough number of particles in any relevant area of interest, millions or even billions of particles might be required for foreseeable applications. This places a strain on both memory resources and time-to-solution when using an existing (thread-) parallel version of NAME.

To allow NAME to be used on larger parallel machines, work by Matt Rigby of the University of Bristol, together with the Met Office and EPCC [2] has developed a distributed memory implementation of NAME. A number of key challenges have been overcome to produce an operational version:

• Particles are split up between the computational resources in a way that balances the amount of work given to each, and also allows all particles in a given geographical area to interact for the purposes of chemistry.

• Particles may need to be transferred between resources as they move around the computational domain, requiring communication via the message passing interface.

• Appropriate results must be aggregated and output for user analysis.

All this work allows significantly higher numbers of particles to be modelled. This should allow workers at universities and government agencies to use NAME in conjunction with higher resolution meteorological data which are now becoming available [3] .

One can hope that this would help mitigate the effects of accidents such as Chernobyl and eruptions such as Eyjafjallajökull.

Notes/references

1. https://www.metoffice.gov.uk/ research/modelling-systems/ dispersion-model

2. The work was funded under the embedded CSE programme of the ARCHER UK National Supercomputing Service (http:// www.archer.ac.uk).

3. NAME is available under licence from the Met Office. The distributed memory version will be available in a future release.

© iStock.com/Nordroden

Kevin Stratford, EPCC Software Architect k.stratford@epcc.ed.ac.uk

Ben Devenish, UK Met Office ben.devenish@metoffice.gov.uk