Author/Authors :
Andreas Becker، نويسنده , , Gerhard Wotawa، نويسنده , , Lars-Erik De Geer، نويسنده , , Petra Seibert، نويسنده , , Roland R. Draxler، نويسنده , , Craig Sloan، نويسنده , , Réal D’amours، نويسنده , , Matthew Hort، نويسنده , , Hubert Glaab، نويسنده , , Philippe Heinrich، نويسنده , , Yves Grillon، نويسنده , , Vyacheslav Shershakov، نويسنده , , Keiichi Katayama، نويسنده , , Yuetang Zhang، نويسنده , , Paul Stewart and Visakan Kadirkamanathan، نويسنده , , Marcus Hirtl، نويسنده , , Michel Jean، نويسنده , , Peter Chen، نويسنده ,
Abstract :
In this paper, we introduce a methodology for quality assessment of backtracking models. We present results illustrating the level of agreement between the backtracking models, and the accuracy of each model and the ensemble model in resolving the geo-temporal reference of a single point source. Both assessments are based on an ensemble of 12 different Lagrangian particle dispersion modelling (LPDM) systems utilized in receptor oriented (adjoint) mode during an international numerical experiment dedicated to source region estimation.
As major result, we can confirm that the findings of Galmarini et al. [2004b. Ensemble prediction forecasting—Part II: application and evaluation. Atmospheric Environment 38, 4619–4632] and Delle Monache and Stull [2003. An ensemble air-quality forecast over Europe during an ozone episode. Atmospheric Environment 37, 3469–3474], regarding the superiority of the ensemble dispersion forecast over a single forecast, do also apply to LPDM when utilized for backtracking purposes, in particular if only vague a priori knowledge of the source time is available. This, however, is a likely situation in the context of the global nuclear monitoring performed by the Provisional Technical Secretariat (PTS) of the Comprehensive Nuclear-Test-Ban Treaty Organization (CTBTO), where quick but reliable source location identification is required. We introduce a simple methodology as a template for a future electronic emergency response system in the field of dispersion modelling.
Keywords :
Long-range Lagrangian dispersion models , Multi-model backward ensemble dispersion modelling , Inversion model evaluation , Global nuclear monitoring