The knowledge of tropospheric water vapor distribution can significantly improve the accuracy of Numerical Weather Prediction (NWP) models. The present work proposes an automatic and fast procedure for generating reliable water vapor products from the synergic use of Sentinel-1 Synthetic Aperture Radar (SAR) imagery and Global Navigation Satellite System (GNSS) observations. Moreover, a compression method able to drastically reduce, without significant accuracy loss, the water vapor dataset dimension has been implemented to facilitate the sharing through cloud services. The activities have been carried in the EU H2020 TWIGA project framework, aimed at providing water vapor maps at Technology Readiness Level 7.
A NOVEL PROCEDURE FOR GENERATION OF SAR-DERIVED ZTD MAPS FOR WEATHER PREDICTION: APPLICATION TO SOUTH AFRICA USE CASE
Molinari, M. E.;Manzoni, M.;Petrushevsky, N.;Venuti, G.;Meroni, A. N.;Mascitelli, A.;
2021-01-01
Abstract
The knowledge of tropospheric water vapor distribution can significantly improve the accuracy of Numerical Weather Prediction (NWP) models. The present work proposes an automatic and fast procedure for generating reliable water vapor products from the synergic use of Sentinel-1 Synthetic Aperture Radar (SAR) imagery and Global Navigation Satellite System (GNSS) observations. Moreover, a compression method able to drastically reduce, without significant accuracy loss, the water vapor dataset dimension has been implemented to facilitate the sharing through cloud services. The activities have been carried in the EU H2020 TWIGA project framework, aimed at providing water vapor maps at Technology Readiness Level 7.| File | Dimensione | Formato | |
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isprs-archives-XLIII-B3-2021-405-2021.pdf
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