Data assimilation for short range atmospheric dispersion of radionuclides: a case study of second-order sensitivity.
This article presents the application of variational data assimilation to a simple Gaussian plume model for radionuclides. Adjoint modeling is applied to the model in order to minimize discrepancies between contamination observations and model outputs. The interest of such an approach is to get a better estimation of some parameters such as emissions or dispersion parameters. A second-order analysis is also performed to assess the sensitivity of the optimized parameters to some poorly known parameters. Sensitivity with respect to network design is also done.
Quélo
Denis
D
INRIA ENPC Clime Project, Research Center in Atmospheric Environment (CEREA), Joint Laboratory Ecole Nationale des Ponts et Chaussées/Electricité de France R&D, 6-8 Avenue Blaise Pascal, 77455 Champs sur Marne, France.
Sportisse
Bruno
B
Isnard
Olivier
O
D000392:Air Movements; D003627:Data Interpretation, Statistical; D015233:Models, Statistical; D016011:Normal Distribution; D011847:Radioactive Fallout / Q000032:analysis*; D011868:Radioisotopes / Q000032:analysis*
D011847:Radioactive Fallout; D011868:Radioisotopes