Section: New Results

Uncertainty quantification

Many uncertainties limit the forecast skills of geophysical simulations: limited understanding of physical phenomena, simplified representation of a system state and of the physical processes, inaccurate data and approximate numerical solutions. In many applications, a deterministic forecast or analysis is not enough a result since its uncertainties may be very large. It is of high interest to evaluate the quality of a forecast, before observations are available, and the quality of an analysis at any location, observed or not. An even more desirable result is the full probability density of system state, which can only be derived from a fully stochastic approach.

Sensitivity analysis in the dispersion of radionuclides

Participants : Sylvain Girard [IRSN] , Vivien Mallet, Irène Korsakissok [IRSN] .

We carried out a sensitivity analysis of the dispersion of radionuclides during Fukushima disaster. We considered the dispersion at regional scale, with the Eulerian transport model Polair3D from Polyphemus. The sensitivities to most input parameters were computed using the Morris method (with 8 levels and 100 trajectories). The influences of 19 scalar parameters were quantified. The scalar parameters were additive terms or multiplicative factors applied to 1D, 2D or 3D fields such as emission rates, precipitations, cloud height, wind velocity. It was shown that, depending on the output quantities of interest (various aggregated atmospheric and ground dose rates), the sensitivity to the inputs may greatly vary. Very few parameters show low sensitivity in any case. The vertical diffusion coefficient, the scavenging factors, the winds and precipitation intensity were found to be the most influential inputs. Most input variables related to the source term (emission rates, emission dates) also had a strong influence.