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Accurate Estimation of Atmospheric Water Vapor Using GNSS Observations and Surface Meteorological Data
Remote sensing data have been increasingly used to measure the content of water vapor in the atmosphere and to characterize its temporal and spatial variations. In this paper, we use observations from Global Navigation Satellite System(s) (GNSS) to estimate time series of precipitable water vapor (PWV) by applying the technique of precise point positioning. For an accurate quantification of the absolute PWV, it is necessary to combine the GNSS observations with meteorological data measured directly or inferred at the GNSS site. In addition, measurements of the surface temperature are used to calculate the empirical constant required to convert the GNSS-based delay into water vapor. Our results show strong agreement between the total precipitable water estimated based on GNSS observations and that measured by the sensor MEdium Resolution Imaging Spectrometer with a mean RMS value of 0.98 mm. In a similar way, we compared the GNSS-based total PWV estimates with those produced by the Weather Research and Forecasting (WRF) Modeling System. We found that the WRF model simulations agree well with the GNSS estimates with a mean RMS value of 0.97 mm.
Accurate Estimation of Atmospheric Water Vapor Using GNSS Observations and Surface Meteorological Data
Remote sensing data have been increasingly used to measure the content of water vapor in the atmosphere and to characterize its temporal and spatial variations. In this paper, we use observations from Global Navigation Satellite System(s) (GNSS) to estimate time series of precipitable water vapor (PWV) by applying the technique of precise point positioning. For an accurate quantification of the absolute PWV, it is necessary to combine the GNSS observations with meteorological data measured directly or inferred at the GNSS site. In addition, measurements of the surface temperature are used to calculate the empirical constant required to convert the GNSS-based delay into water vapor. Our results show strong agreement between the total precipitable water estimated based on GNSS observations and that measured by the sensor MEdium Resolution Imaging Spectrometer with a mean RMS value of 0.98 mm. In a similar way, we compared the GNSS-based total PWV estimates with those produced by the Weather Research and Forecasting (WRF) Modeling System. We found that the WRF model simulations agree well with the GNSS estimates with a mean RMS value of 0.97 mm.
Accurate Estimation of Atmospheric Water Vapor Using GNSS Observations and Surface Meteorological Data
Alshawaf, F (Autor:in) / Fuhrmann, T / Knopfler, A / Luo, X / Mayer, M / Hinz, S / Heck, B
2015
Aufsatz (Zeitschrift)
Englisch
Lokalklassifikation TIB:
770/3710/5670
BKL:
38.03
Methoden und Techniken der Geowissenschaften
/
74.41
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