Low-Level Jet observational study for the Brazilian Nuclear Reactor region

• Autor(a) principal: BEU, CASSIA M.L.
• Data de Publicação: 2019
• Outros Autores: ESPINDOLA, FELIPE D.C., LANDULFO, EDUARDO, REMOTE SENSING OF CLOUDS AND THE ATMOSPHERE, 23th
• Tipo de documento: Artigo de conferência
• Título da fonte: Repositório Institucional do IPEN
• Texto Completo: http://repositorio.ipen.br/handle/123456789/29468
• topic: atmospheres; planetary atmospheres; wind loads; jets; fluid flow; boundary layers; brazil; dispersions; nuclear facilities; rmb reactor; isotope separation plants; atmospheric precipitations; meteorology

A doppler wind lidar was employed to investigate the features of the Low-Level Jet (LLJ) at Ipero, Sao Paulo State, Brazil. The Ipero Municipality already host a nuclear facility for uranium enrichment and a new plant, a nuclear reactor, is planned to be built there. The nuclear activities require a good understanding of atmospheric dispersion, as for normal operation conditions as for accidental emissions. The LLJ is a natural phenomenon that may occur within the Planetary Boundary Layer and plays an important role for the atmospheric dispersion. Knowing the LLJ characteristics is essential to evaluate the performances of the weather forecast models that are used as input for the atmospheric dispersion models. The field campaign results showed that the LLJs occur with high frequency at Ipero and that the Stable Boundary Layer (SBL) is shallow, which in turn is unfavored for pollutant dilution because all surface emissions remain confined within the SBL. The 2 weather forecast models evaluated didn??t reproduce the LLJ, despite their high horizontal resolution. The numerical models also underestimated the wind speed. Both the LLJ and the wind speed are key parameters for dispersion simulations. As the weather forecast models diverge of the observational data, they must be better parameterized for provide reliable simulations before being adopted as input for any atmospheric dispersion models. The field campaign (planned to extend for 1 year) data are essential for the parameterization of the numerical models.