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Development of an improved empirical model for slant delays in the troposphere (GPT2w)
Development of an improved empirical model for slant delays in the troposphere (GPT2w)
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Development of an improved empirical model for slant delays in the troposphere (GPT2w)
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Development of an improved empirical model for slant delays in the troposphere (GPT2w)
Development of an improved empirical model for slant delays in the troposphere (GPT2w)

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Development of an improved empirical model for slant delays in the troposphere (GPT2w)
Development of an improved empirical model for slant delays in the troposphere (GPT2w)
Journal Article

Development of an improved empirical model for slant delays in the troposphere (GPT2w)

2015
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Overview
Global pressure and temperature 2 wet (GPT2w) is an empirical troposphere delay model providing the mean values plus annual and semiannual amplitudes of pressure, temperature and its lapse rate, water vapor pressure and its decrease factor, weighted mean temperature, as well as hydrostatic and wet mapping function coefficients of the Vienna mapping function 1. All climatological parameters have been derived consistently from monthly mean pressure level data of ERA-Interim fields (European Centre for Medium-Range Weather Forecasts Re-Analysis) with a horizontal resolution of 1°, and the model is suitable to calculate slant hydrostatic and wet delays down to 3° elevation at sites in the vicinity of the earth surface using the date and approximate station coordinates as input. The wet delay estimation builds upon gridded values of the water vapor pressure, the weighted mean temperature, and the water vapor decrease factor, with the latter being tuned to ray-traced zenith wet delays. Comparisons with zenith delays at 341 globally distributed global navigation satellite systems stations show that the mean bias over all stations is below 1 mm and the mean standard deviation is about 3.6 cm. The GPT2w model with the gridded input file is provided at http://ggosatm.hg.tuwien.ac.at/DELAY/SOURCE/GPT2w/.