{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T07:42:27Z","timestamp":1760254947002},"reference-count":33,"publisher":"Walter de Gruyter GmbH","issue":"1","license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022,12,23]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Zenith Tropospheric Delays (ZTDs) are used to correct tropospheric effects that cause a delay in the signal measured by Global Navigation Satellite Systems (GNSS) receivers and obtain accurate measurements. ZTD can be estimated from GNSS processing, which means they may suffer from occasional or systematic errors. Therefore, it is necessary to assess the quality and stability of these data over time, since ZTDs are used in several applications that require centimeter precision. Within this context, this work aims to assess the available ZTD of the whole Geodetic Reference System for the Americas Continuously Operating Network (SIRGAS-CON), consisting of 467 stations, spanning the period from January 2014 to December 2020 using the most recent Numerical Weather Model ERA5 from the European Centre for Medium-Range Weather Forecasts and common stations to the International GNSS Service (IGS) for an intercomparison. Results show that 10% of the stations present some instability, such as periods of highly dispersed data or discontinuities, with more occurrence in stations located in Argentina, Uruguay and Colombia. The remaining 90% proved to have stable and reliable ZTD, both in comparison with ERA5 and IGS.<\/jats:p>","DOI":"10.1515\/jogs-2022-0144","type":"journal-article","created":{"date-parts":[[2022,12,23]],"date-time":"2022-12-23T11:29:01Z","timestamp":1671794941000},"page":"195-210","source":"Crossref","is-referenced-by-count":2,"title":["Assessment of SIRGAS-CON tropospheric products using ERA5 and IGS"],"prefix":"10.1515","volume":"12","author":[{"given":"Anderson","family":"Prado","sequence":"first","affiliation":[{"name":"Faculty of Sciences of University of Porto (FCUP), DGAOT, University of Porto , Rua do Campo Alegre s\/n , 4169-007 Porto , Portugal"}]},{"given":"Telmo","family":"Vieira","sequence":"additional","affiliation":[{"name":"Faculty of Sciences of University of Porto (FCUP), DGAOT, University of Porto , Rua do Campo Alegre s\/n , 4169-007 Porto , Portugal"},{"name":"Interdisciplinary Centre of Marine and Environmental Research (CIIMAR), Terminal de Cruzeiros do Porto de Leix\u00f5es, Av. General Norton de Matos s\/n , 4450-208 Matosinhos , Portugal"}]},{"given":"Maria Joana","family":"Fernandes","sequence":"additional","affiliation":[{"name":"Faculty of Sciences of University of Porto (FCUP), DGAOT, University of Porto , Rua do Campo Alegre s\/n , 4169-007 Porto , Portugal"},{"name":"Interdisciplinary Centre of Marine and Environmental Research (CIIMAR), Terminal de Cruzeiros do Porto de Leix\u00f5es, Av. General Norton de Matos s\/n , 4450-208 Matosinhos , Portugal"}]}],"member":"374","published-online":{"date-parts":[[2022,12,23]]},"reference":[{"key":"2023010906354229271_j_jogs-2022-0144_ref_001","doi-asserted-by":"crossref","unstructured":"Bento, V. A., C. C. DaCamara, I. F. Trigo, J. Martins, and A. 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