the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Decadal variations in atmospheric water vapor time series estimated using ground-based GNSS
Abstract. Ground-based GNSS (Global Navigation Satellite Systems) have efficiently been used since the 1990s as a meteorological observing system. Recently scientists used GNSS time series of precipitable water vapor (PWV) for climate research. In this work, we use time series from GNSS, European Center for Medium-Range Weather Forecasts Reanalysis (ERA-Interim) data, and meteorological measurements to evaluate climate evolution in Central Europe. The assessment of climate change requires monitoring of different atmospheric variables such as temperature, PWV, precipitation, and snow cover. PWV time series were obtained by three methods: 1) estimated from ground-based GNSS observations using the method of precise point positioning, 2) inferred from ERA-Interim data, and 3) determined based on daily surface measurements of temperature and relative humidity. The other variables are available from surface meteorological stations or received from ERA-Interim. The PWV trend component estimated from GNSS data strongly correlates with that estimated from the other data sets. The linear trend is estimated by straight line fitting over 30 years of seasonally-adjusted PWV time series obtained using meteorological measurements. The results show a positive trend in the PWV time series at more than 60 GNSS sites with an increase of 0.3–0.6 mm/decade. In this paper, we compare the results of three stations. The temporal increment of the PWV correlates with the temporal increase in the temperature levels.
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RC1: 'Comments to "Decadal variations in atmospheric water vapor time series estimated using ground-based GNSS"', Anonymous Referee #1, 23 Jun 2016
- AC1: 'Response of the authors', Fadwa Alshawaf, 17 Aug 2016
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RC2: 'Reviewer Comments', Anonymous Referee #2, 02 Jul 2016
- AC2: 'Response of the authors', Fadwa Alshawaf, 18 Aug 2016
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RC3: 'Comments on « Decadal Variations in atmospheric water vapor time series estimated using ground-based GNSS »', Anonymous Referee #3, 07 Jul 2016
- AC3: 'Response of the authors', Fadwa Alshawaf, 18 Aug 2016
-
RC1: 'Comments to "Decadal variations in atmospheric water vapor time series estimated using ground-based GNSS"', Anonymous Referee #1, 23 Jun 2016
- AC1: 'Response of the authors', Fadwa Alshawaf, 17 Aug 2016
-
RC2: 'Reviewer Comments', Anonymous Referee #2, 02 Jul 2016
- AC2: 'Response of the authors', Fadwa Alshawaf, 18 Aug 2016
-
RC3: 'Comments on « Decadal Variations in atmospheric water vapor time series estimated using ground-based GNSS »', Anonymous Referee #3, 07 Jul 2016
- AC3: 'Response of the authors', Fadwa Alshawaf, 18 Aug 2016
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Cited
6 citations as recorded by crossref.
- Inter-annual variability of variations of ground and integrated atmospheric water vapor content in Europe O. Khutorova et al. 10.1088/1755-1315/107/1/012031
- An Advanced Algorithm to Retrieve Total Atmospheric Water Vapor Content From the Advanced Microwave Scanning Radiometer Data Over Sea Ice and Sea Water Surfaces in the Arctic E. Zabolotskikh et al. 10.1109/TGRS.2019.2948289
- Precipitable water vapor characterization in the coastal regions of China based on ground-based GPS Z. Wang et al. 10.1016/j.asr.2017.09.017
- Analysis of temporal and spatial variations of total precipitable water vapor in western Iran using radiosonde and MODIS measurements M. Merrikhpour & M. Rahimzadegan 10.1117/1.JRS.13.044508
- Application of GNSS derived precipitable water vapour prediction in West Africa A. Acheampong & K. Obeng 10.1515/jogs-2019-0005
- Spatiotemporal variability of water vapor over Turkey from GNSS observations during 2009–2017 and predictability of ERA-Interim and ARMA model K. Ansari et al. 10.1186/s41445-018-0017-4