Processos convectivos identificados por uma microrrede de estações automáticas de superfície

• Ano de defesa: 2020
• Autor(a) principal: Feldhaus, Patricia Fernanda
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal de Santa Maria; Brasil; Meteorologia; UFSM; Programa de Pós-Graduação em Meteorologia; Centro de Ciências Naturais e Exatas
• Palavras-chave em Português: Meteorologia de mesoescala; Microrrede de observação meteorológica de superfície; Tempestades convectivas locais; Mesoscale meteorology; Surface meteorological observation network; Local convective storms; CNPQ::CIENCIAS EXATAS E DA TERRA::GEOCIENCIAS::METEOROLOGIA
• Link de acesso: http://repositorio.ufsm.br/handle/1/22380

This study explored surface automated weather systems that sample and record data in high frequency to demonstrate the importance of this strategy of data collection in the characterization and monitoring of atmospheric disturbances generated by convective storms. To that end, data from a micrometeorological tower, an adaptive micronet of surface stations, and a portable meteorological station designed for monitoring convective phenomena (Mesomóvel station) were analyzed for a number of situations in which deep convection was observed over these stations. Time series of atmospheric pressure, air temperature, and wind gusts produced at high sampling frequency were investigated to assess the value added by these data in the characterization of surface circulations generated by storms, in comparison with hourly observations from the operational network maintained by INMET. One hypothesis tested was whether the 1st and 99th percentiles of the rates of change per minute of pressure and temperature displayed any skill in discriminating between the fast mode of variation associated with convective circulations and the slow mode of variation of the background synoptic scale. The results highlighted the important value added by the high frequency measurements performed with the special stations in the characterization of disturbances in temperature, pressure and winds generated by deep convection, such as gust fronts, cold pools, mesohighs and mesolows, including non-hydrostatic mechanismos affecting the pressure disturbances. None of the convectively-generated disturbances was adequately characterized by the hourly reports from INMET automated stations situated in the same observing sites or in the vicinities of the special stations. The time series analysis of the rates of change of pressure and temperature contributed to better detect the passage of the convectively-induced disturbances. However, it was shown that the 1st and 99th percentiles of these rates of change can also be attained in the absence of convective storms and other sub-synoptic disturbances.