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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 10, issue 9 | Copyright
Atmos. Meas. Tech., 10, 3117-3132, 2017
https://doi.org/10.5194/amt-10-3117-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Research article 31 Aug 2017

Research article | 31 Aug 2017

Estimating trends in atmospheric water vapor and temperature time series over Germany

Fadwa Alshawaf1, Kyriakos Balidakis2, Galina Dick1, Stefan Heise1, and Jens Wickert1,2 Fadwa Alshawaf et al.
  • 1German Research Centre for Geosciences GFZ, Telegrafenberg, 14473 Potsdam, Germany
  • 2Institute of Geodesy and Geoinformation Science, Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin, Germany

Abstract. Ground-based GNSS (Global Navigation Satellite System) has efficiently been used since the 1990s as a meteorological observing system. Recently scientists have used GNSS time series of precipitable water vapor (PWV) for climate research. In this work, we compare the temporal trends estimated from GNSS time series with those estimated from European Center for Medium-Range Weather Forecasts (ECMWF) reanalysis (ERA-Interim) data and meteorological measurements. We aim to evaluate climate evolution in Germany by monitoring different atmospheric variables such as temperature and PWV. 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 reanalysis data, and (3) determined based on daily in situ measurements of temperature and relative humidity. The other relevant atmospheric parameters are available from surface measurements of meteorological stations or derived from ERA-Interim. The trends are estimated using two methods: the first applies least squares to deseasonalized time series and the second uses the Theil–Sen estimator. The trends estimated at 113 GNSS sites, with 10 to 19 years temporal coverage, vary between −1.5 and 2.3mmdecade−1 with standard deviations below 0.25mmdecade−1. These results were validated by estimating the trends from ERA-Interim data over the same time windows, which show similar values. These values of the trend depend on the length and the variations of the time series. Therefore, to give a mean value of the PWV trend over Germany, we estimated the trends using ERA-Interim spanning from 1991 to 2016 (26 years) at 227 synoptic stations over Germany. The ERA-Interim data show positive PWV trends of 0.33±0.06mmdecade−1 with standard errors below 0.03mmdecade−1. The increment in PWV varies between 4.5 and 6.5% per degree Celsius rise in temperature, which is comparable to the theoretical rate of the Clausius–Clapeyron equation.

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In this paper, we aimed at estimating climatic trends using precipitable water vapor time series and surface measurements of air temperature in Germany. We used GNSS, ERA-Interim, and synoptic data. The results show mainly a positive trend in precipitable water vapor and temperature with an increase in the trend when moving to northeastern Germany.
In this paper, we aimed at estimating climatic trends using precipitable water vapor time series...
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