Desenvolvimento de um programa para caracterização de eventos oceânicos/atmosféricos: aplicações usando parâmetros característicos do oceano atlântico tropical e dados da estações GNSS e meteorológica de Natal-RN, Brasil

Abstract

Among several factors that influence artificial satellite positioning of GNSS (Global Navigation Satellite System), the Zenithal Tropospheric Delay (ZTD) stands out, it is basically the sum of two components, the hydrostatic (ZHD - Zenithal Hydrostatic Delay) influenced predominantly by nitrogen and oxigen, and wet component (ZWD - Zenithal Wet Delay) influenced by the water vapour in the Troposphere. These components could be calculated from GNSS Gauge stations signals observations. The wet component has strong relation with IWV (Integrated Water Vapour) in the atmosphere. This study aims to develop a guide user interface that enable databases generation using IWV obtained through radiofrequency signals of any GNSS station, and relate it with oceanic and meteorologic variables. The software named PROCEOS (Programa de Caracterização de Eventos Oceânicos Atmosféricos), has as differential when compared to similar programs, a friendly use structure. It has a multifunctional structure, other than that enable the user to manipulate reanalyses datas like provided by ECMWF (European Center for Medium Range Forecasts), as well as spatial and temporal distribuitions of these variables – maps and time series even at surface as in pressure levels – besides of filtering and statistics analysis of outputs, like correlation between variables. Analysis were performed with PROCEOS using signals from GNSS RNNA in INPE (National Institute for Space Research) near to UFRN campus Central, and Meteorological Natal-304 stations,in Central UFRN Campus, Natal-Brazil in order to predict precipitation over Natal (RN). PROCEOS produced satisfactory results relating to similar softwares. This tecnique has showed as an alternative and promising for nowcasting forecasts, moreover its results can be use as input data for meteorological models forecasts.