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PWV Estimation Using GPS and its Comparison with INSAT-3D Rainfall Data

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Abstract

Precipitable water vapor (PWV) plays an important role in understanding the atmosphere and weather. The advancement in Global Navigation Satellite System (GNSS) technology provides the possibility of computing PWV in near real time. In this study, the PWV was computed using the Zenith Tropospheric Delay (ZTD) from Global Positioning System (GPS) data for two International GNSS Service (IGS) stations (IISC & HYDE) for monsoon period (June–September) of 2014 and 2015. The GPS-derived PWV has been validated with reference to radiosonde data and University NAVSTAR Consortium (UNAVCO) PWV products. The coefficient of determination between GPS-derived PWV and radiosonde PWV is 0.73–0.83 for IISC station and 0.76–0.91 for HYDE station. For IISC station, the coefficient of determination between GPS-derived PWV and UNAVCO-derived PWV is 0.80–0.89. Also, in this study, GPS-derived PWV for IISC station has been compared with the rainfall events of Indian National Satellite System (INSAT-3D). From the analysis, we observed a direct relation between PWV and rainfall events from Hydro Estimator Method (HEM), INSAT Multi spectral Rainfall (IMR) products of INSAT-3D. This study highlights the satellite-based observations from GNSS and INSAT satellite for regional weather forecasting in near real time.

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Acknowledgements

We thank IGS for providing GNSS data which was obtained through the online archives of the Crustal Dynamics Data Information System (CDDIS), NASA, Goddard Space Flight Center, Green belt, MD, USA.(ftp://cddis.gsfc.nasa.gov) and also thanked India Meteorological Department for providing Automatic Weather Station data. We extend our sincere thanks to Saritha PK, NRSC. for her support in INSAT-3D (IMR and HEM) rainfall data analysis. The INSAT-3D data are available in the public domain from the portal www.mosdac.gov.in.

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Correspondence to Sravanthi Gunti.

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Gunti, S., Narendran, J. & Muralikrishnan, S. PWV Estimation Using GPS and its Comparison with INSAT-3D Rainfall Data. J Indian Soc Remote Sens 49, 1453–1460 (2021). https://doi.org/10.1007/s12524-021-01324-7

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