Dispersion modelling at RMIB
Royal Meteorological Institute of Belgium
Contact: Andy Delcloo
The consequenses, related to the volcanic eruption of the Eyjafjallajökull, were a major incentive for the meteorological- and other scientific communities to improve their operational products related to these types of events.
At the RMI, we have set up a strategy to improve our knowledge on aerosols, observed from the surface by setting up a LIDAR network. One of the major problems during this event was the lack of knowledge on the observation of the vertical distribution of aerosols in the atmosphere. Since the installation of our operational LIDAR network, we have the possibility to observe aerosols in the atmosphere.
RMI is also responsible for the calculation of dispersion of suspended nuclear particles. Therefore we have an operational dispersion model at our disposal, which calculates for several hotspots on a daily basis precalculated dispersion maps. We can use the dispersion model also for other types of aerosols and trace gases (e.g. SO2, see Fig. 1)).
In the weather office, the forecasters can start an "on-demand" dispersion modelling forecast which can be calculated for every location, located on the Northern Hemispere. We can provide a forecast with a lead time of 72 hours.
On 22/09/2014, our brewer spectrofotometer observed a total column of 7 DU of SO2. This was nicely forecasted by our dispersion model (Figure 1).
Example of a dispersion simulation for the Bardarbunga volcano (20/09/2015)
Ph D project on Uncertainty quantification in long range lagrangian atmospheric transport and dispersion modelling
Pieter De Meutter
contact: Pieter De Meutter
In collaboration with the Royal Meteorological Institute and the CTBTO the dispersion model FLEXPART with Numerical Weather Prediction input from the ECMWF at a global scale and a horizontal resolution of 0.5 degrees will be further made operational to perform the necessary calculations for the uncertainty quantification.
A study will be made on the sensitivity of the model results as a function of model parameters over the realistic physical range. In this way most important factors influencing the model uncertainty will be identified.
In order to assess the uncertainty of changing weather conditions on the modelling dispersion results, FLEXPART will to be set-up to run with the 50 members of the ECMWF Ensemble Prediction System (EPS), which are intelligently designed to take into account uncertainty in numerical weather forecast. This will make it possible to assess for each species under consideration an uncertainty analysis.
To use this uncertainty information in an operational context, an algorithm will be designed to incorporate this NWP uncertainty for the species under consideration in the operational model which only uses the deterministic ECMWF input, since it is computationally very expensive to run the dispersion model ingesting the 50 EPS members into FLEXPART.
To contribute to the identification of the most important sources of uncertainty and to determine in the end the relevance of the uncertainty quantification one or more cases will be analyzed. These cases can include the North-Korean nuclear bomb tests, the Fukushima nuclear accident and releases from radiopharmaceutical facilities in normal operation. For all of these cases high quality data from the radionuclide component (including noble gas component) of the International Monitoring System can be used.
More information can be found on the website of SCK-CEN