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A large set of images, in different weather conditions, produced by Sentinel\u20101A in a very well monitored region near the Appalachian Mountains, are assimilated by the Weather Research and Forecast (WRF) model. Results covering more than 2\u00a0years of operation indicate a consistent improvement of the water vapor predictability up to a range comparable with the transit time of the air mass in the synthetic aperture radar interferograms footprint, an overall improvement in the forecast of different precipitation events, and better representation of the spatial distribution of precipitation. This result highlights the significant potential for increasing short\u2010range atmospheric predictability from improved high\u2010resolution precipitable water vapor initial data, which can be obtained from new high\u2010resolution all\u2010weather microwave sensors.<\/jats:p>","DOI":"10.1029\/2018gl081336","type":"journal-article","created":{"date-parts":[[2019,2,26]],"date-time":"2019-02-26T23:00:12Z","timestamp":1551222012000},"page":"2949-2955","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":30,"title":["InSAR Meteorology: High\u2010Resolution Geodetic Data Can Increase Atmospheric Predictability"],"prefix":"10.1029","volume":"46","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4288-9456","authenticated-orcid":false,"given":"P. M. 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