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@Article{AlvesSaMaSoGoMa:2015:UsReNu,
               author = "Alves, Daniele Barroca Marra and Sapucci, Luiz Fernando and 
                         Marques, Haroldo Antonio and Souza, Eniuce Menezes de and Gouveia, 
                         Tayn{\'a} Aparecida Ferreira and Mag{\'a}rio, Jackes Akira",
          affiliation = "{Universidade Estadual Paulista (UNESP)} and {Instituto Nacional 
                         de Pesquisas Espaciais (INPE)} and {Universidade Federal de 
                         Pernambuco (UFPE)} and {Universidade Estadual de Maring{\'a} 
                         (UEM)} and {Universidade Estadual Paulista (UNESP)} and 
                         {Universidade Estadual Paulista (UNESP)}",
                title = "Using a regional numerical weather prediction model for GNSS 
                         positioning over Brazil",
              journal = "GPS Solutions",
                 year = "2015",
               volume = "x",
             keywords = "Numerical weather prediction, Zenithal tropospheric delay, GNSS, 
                         Positioning.",
             abstract = "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.",
                  doi = "10.1007/s10291-015-0477-x",
                  url = "http://dx.doi.org/10.1007/s10291-015-0477-x",
                 issn = "1080-5370 and 1521-1886",
             language = "en",
        urlaccessdate = "29 nov. 2020"
}


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