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Despite the limitations resulting from the 6\u2010day return period of images produced by the 2\u2010satellite system, it is found that for a sufficiently large domain designed to contain a set of images every 12\u00a0h (at varying locations), the impact on model performance is beneficial or at least neutral. The proposed methodology is tested in 24 consecutive 12\u00a0h forecasts, covering two cycles of the Sentinel\u20101 system and 214 images, for a domain containing Iberia. A statistical analysis of the forecast precipitable water vapor (PWV) against independent GNSS observations concluded for relevant improvements in the different scores, especially during a consecutive 3\u2010day period where the standard initial data were less accurate. An analysis of the rain forecasts against gridded remote sensing observations further indicates an overall improvement in the grid\u2010point distribution of different precipitation classes throughout the simulation, even when the mean impact of PWV assimilation was not significant. It is suggested that current InSAR data are already a useful source of NWP data and will only become more relevant as new systems are put into operation.<\/jats:p>","DOI":"10.1029\/2020jd034171","type":"journal-article","created":{"date-parts":[[2021,1,17]],"date-time":"2021-01-17T15:24:33Z","timestamp":1610897073000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["Continuous Multitrack Assimilation of Sentinel\u20101 Precipitable Water Vapor Maps for Numerical Weather Prediction: How Far Can We Go With Current InSAR Data?"],"prefix":"10.1029","volume":"126","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8027-2142","authenticated-orcid":false,"given":"P.","family":"Mateus","sequence":"first","affiliation":[{"name":"Instituto Dom Luiz Faculdade de Ci\u00eancias Universidade de Lisboa  Lisbon Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4288-9456","authenticated-orcid":false,"given":"P. M. A.","family":"Miranda","sequence":"additional","affiliation":[{"name":"Instituto Dom Luiz Faculdade de Ci\u00eancias Universidade de Lisboa  Lisbon Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7621-5014","authenticated-orcid":false,"given":"G.","family":"Nico","sequence":"additional","affiliation":[{"name":"Istituto per le Applicazioni del Calcolo Consiglio Nazionale delle Ricerche  Bari Italy"},{"name":"Department of Cartography and Geoinformatics Institute of Earth Sciences Saint Petersburg State University (SPSU)  Saint Petersburg Russia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1028-4644","authenticated-orcid":false,"given":"J.","family":"Catalao","sequence":"additional","affiliation":[{"name":"Instituto Dom Luiz Faculdade de Ci\u00eancias Universidade de Lisboa  Lisbon Portugal"}]}],"member":"13","published-online":{"date-parts":[[2021,2,5]]},"reference":[{"key":"e_1_2_7_2_1","volume-title":"A Three\u2010dimensional variational (3DVAR) data assimilation system for use with MM5","author":"Barker D. 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