Busca avançada
Ano de início
Entree
(Referência obtida automaticamente do Web of Science, por meio da informação sobre o financiamento pela FAPESP e o número do processo correspondente, incluída na publicação pelos autores.)

Using a regional numerical weather prediction model for GNSS positioning over Brazil

Texto completo
Autor(es):
Marra Alves, Daniele Barroca ; Sapucci, Luiz Fernando ; Marques, Haroldo Antonio ; de Souza, Eniuce Menezes ; Ferreira Gouveia, Tayna Aparecida ; Magario, Jackes Akira
Número total de Autores: 6
Tipo de documento: Artigo Científico
Fonte: GPS SOLUTIONS; v. 20, n. 4, p. 677-685, OCT 2016.
Citações Web of Science: 4
Resumo

The global navigation satellite system (GNSS) can provide centimeter positioning accuracy at low costs. However, in order to obtain the desired high accuracy, it is necessary to use high-quality atmospheric models. We focus on the troposphere, which is an important topic of research in Brazil where the tropospheric characteristics are unique, both spatially and temporally. There are dry regions, which lie mainly in the central part of the country. However, the most interesting area for the investigation of tropospheric models is the wet region which is located in the Amazon forest. This region substantially affects the variability of humidity over other regions of Brazil. It provides a large quantity of water vapor through the humidity convergence zone, especially for the southeast region. The interconnection and large fluxes of water vapor can generate serious deficiencies in tropospheric modeling. The CPTEC/INPE (Center for Weather Forecasting and Climate Studies/Brazilian Institute for Space Research) has been providing since July 2012 a numerical weather prediction (NWP) model for South America, known as Eta. It has yield excellent results in weather prediction but has not been used in GNSS positioning. This NWP model was evaluated in precise point positioning (PPP) and network-based positioning. Concerning PPP, the best positioning results were obtained for the station SAGA, located in Amazon region. Using the NWP model, the 3D RMS are less than 10 cm for all 24 h of data, whereas the values reach approximately 60 cm for the Hopfield model. For network-based positioning, the best results were obtained mainly when the tropospheric characteristics are critical, in which case an improvement of up to 7.2 % was obtained in 3D RMS using NWP models. (AU)

Processo FAPESP: 12/19906-7 - Avaliação robusta do impacto da modelagem atmosférica no posicionamento baseado em redes
Beneficiário:Daniele Barroca Marra Alves
Modalidade de apoio: Auxílio à Pesquisa - Regular