Evaluation of statistical models in atmospheric dispersion modelling

2000 ◽  
Vol 14 (1/2/3/4/5/6) ◽  
pp. 106
Author(s):  
P.C. Chatwin ◽  
N. Mole
Keyword(s):  
Statistical Models ◽  
Atmospheric Dispersion ◽  
Dispersion Modelling ◽  
Atmospheric Dispersion Modelling

Optimizing the calculation grid for atmospheric dispersion modelling

2015 ◽  
Vol 142 ◽  
pp. 103-112
Author(s):  
S. Van Thielen ◽  
C. Turcanu ◽  
J. Camps ◽  
R. Keppens
Keyword(s):  
Atmospheric Dispersion ◽  
Dispersion Modelling ◽  
Atmospheric Dispersion Modelling ◽  
Calculation Grid

scholarly journals Atmospheric Dispersion Modelling at the London VAAC: A Review of Developments since the 2010 Eyjafjallajökull Volcano Ash Cloud

Atmosphere ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 352 ◽  
Author(s):  
Frances M. Beckett ◽  
Claire S. Witham ◽  
Susan J. Leadbetter ◽  
Ric Crocker ◽  
Helen N. Webster ◽  
...  
Keyword(s):  
Volcanic Ash ◽  
Dispersion Model ◽  
Source Parameters ◽  
Atmospheric Dispersion ◽  
Lessons Learned ◽  
Dispersion Modelling ◽  
Atmospheric Dispersion Modelling ◽  
Volcanic Ash Cloud ◽  
Atmospheric Dispersion Model ◽  
Ash Cloud

It has been 10 years since the ash cloud from the eruption of Eyjafjallajökull caused unprecedented disruption to air traffic across Europe. During this event, the London Volcanic Ash Advisory Centre (VAAC) provided advice and guidance on the expected location of volcanic ash in the atmosphere using observations and the atmospheric dispersion model NAME (Numerical Atmospheric-Dispersion Modelling Environment). Rapid changes in regulatory response and procedures during the eruption introduced the requirement to also provide forecasts of ash concentrations, representing a step-change in the level of interrogation of the dispersion model output. Although disruptive, the longevity of the event afforded the scientific community the opportunity to observe and extensively study the transport and dispersion of a volcanic ash cloud. We present the development of the NAME atmospheric dispersion model and modifications to its application in the London VAAC forecasting system since 2010, based on the lessons learned. Our ability to represent both the vertical and horizontal transport of ash in the atmosphere and its removal have been improved through the introduction of new schemes to represent the sedimentation and wet deposition of volcanic ash, and updated schemes to represent deep moist atmospheric convection and parametrizations for plume spread due to unresolved mesoscale motions. A good simulation of the transport and dispersion of a volcanic ash cloud requires an accurate representation of the source and we have introduced more sophisticated approaches to representing the eruption source parameters, and their uncertainties, used to initialize NAME. Finally, upper air wind field data used by the dispersion model is now more accurate than it was in 2010. These developments have resulted in a more robust modelling system at the London VAAC, ready to provide forecasts and guidance during the next volcanic ash event.

scholarly journals Operationalising an ensemble approach in the description of uncertainty in atmospheric dispersion modelling and an emergency response

2020 ◽  
Vol 55 ◽  
pp. S75-S79
Author(s):  
P. Bedwell ◽  
I. Korsakissok ◽  
S. Leadbetter ◽  
R. Périllat ◽  
Cs. Rudas ◽  
...  
Keyword(s):  
Emergency Response ◽  
Atmospheric Dispersion ◽  
Ensemble Member ◽  
Dispersion Modelling ◽  
Radiological Assessment ◽  
Operational Method ◽  
Complete Model ◽  
Ensemble Approach ◽  
Atmospheric Dispersion Modelling ◽  
Measure Of Uncertainty

Uncertainties were propagated through the chain of atmospheric dispersion and radiological assessment models based on an ensemble approach for a range of scenarios. It was apparent that the time taken to complete model runs, ranging from several hours to a few tens of hours, was not appropriate for an emergency response. Thus, for an operational method, there was a requirement to reduce the number of ensemble members and/or reduce model run time for a single ensemble member, such that a measure of uncertainty may be obtained within the timeframe of one hour, but without significant detriment to the model endpoints derived, the uncertainty estimated and the radiation protection advice inferred. This study proposes recommendations for operationalising an ensemble approach used in the description of uncertainty in atmospheric dispersion modelling and an emergency response.

scholarly journals Multilevel Monte Carlo and improved timestepping methods in atmospheric dispersion modelling

2018 ◽  
Vol 354 ◽  
pp. 320-343 ◽  
Author(s):  
Grigoris Katsiolides ◽  
Eike H. Müller ◽  
Robert Scheichl ◽  
Tony Shardlow ◽  
Michael B. Giles ◽  
...  
Keyword(s):  
Monte Carlo ◽  
Atmospheric Dispersion ◽  
Dispersion Modelling ◽  
Multilevel Monte Carlo ◽  
Atmospheric Dispersion Modelling
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