Um problema inverso em dois passos para estimação de perfis de temperatura na atmosfera com nuvens a partir de medidas de radiância feitas por satélite

• Ano de defesa: 2013
• Autor(a) principal: Soares, Patricia Oliva
• Orientador(a): Silva Neto, Antônio José da
• Banca de defesa: Biondi Neto, Luiz , Moura, Carlos Antonio de , Sacco, Wagner Figueiredo , Galeão, Augusto Cesar Noronha Rodrigues
• Tipo de documento: Tese
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade do Estado do Rio de Janeiro
• Programa de Pós-Graduação: Programa de Pós-Graduação em Modelagem Computacional
• Departamento: Centro de Tecnologia e Ciências::Instituto Politécnico
• País: BR
• Palavras-chave em Português: Problemas inversos; Transferência radiativa; Redes neurais artificiais; Sensoriamento remoto; Perfil de temperatura; Nuvens
• Palavras-chave em Inglês: Inverse problems; Radiative transfer; Artificial neural networks; Remote sensing; Temperature profile; Clouds
• Área do conhecimento CNPq: CNPQ::CIENCIAS EXATAS E DA TERRA::MATEMATICA::MATEMATICA APLICADA
• Link de acesso: http://www.bdtd.uerj.br/handle/1/13652

This thesis presents a methodology for retrieving vertical temperature profiles in the atmosphere with clouds from radiance measurements made by satellite, using artificial neural networks. Vertical temperature profiles are important initial conditions for numerical weather prediction models, and are usually obtained from measurements of radiance using infrared channels. Though, when these measurements are performed in the atmosphere with clouds, it is not possible to retrieve the temperature profile with current techniques. It is a significant loss of information, since on average 20% of the pixels of the images have clouds. In this thesis, this problem is solved as a two-step inverse problem: the first step is an inverse problem of boundary condition estimation, where the radiance reaching the cloud basis is determined from radiance measured by satellite; the second step consists in determining the vertical temperature profile from the boundary condition estimated in the first step. Reconstructions of temperature profile are presented for four test cases. The results show that the proposed methodology produces satisfactory results and has great potential for use, allowing to incorporate information from a wider area of the planet and thus to improve numerical weather prediction models.