Abstract
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 2.3 mm decade−1 with standard deviations below 0.25 mm decade−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 ± 0.06 mm decade−1 with standard errors below 0.03 mm decade−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.
Highlights
Water vapor is considered the most active greenhouse gas that permanently affects the Earth’s climate
Since the possibility for obtaining a data set with long time series and high spatial resolution for estimating precipitable water vapor (PWV) trends is very limited, we evaluated the potential of this method for climate analysis
We aimed at estimating climatic trends from GNSS-based precipitable water vapor time series and surface measurements of air temperature in Germany
Summary
Water vapor is considered the most active greenhouse gas that permanently affects the Earth’s climate. Due to its high temporal and spatial variations, the precipitable water vapor (PWV) content in the atmosphere has to be regularly and accurately determined for meteorological and climatological purposes. While other observation systems such as radiosondes and microwave radiometers provide PWV measurements that are limited in the temporal and (or) spatial resolutions, ground-based GNSSs provide time series of accurate PWV estimates with 15 min (for this work) sampling at dense GNSS networks, without significant additional costs. Since Bevis et al (1992) presented the Global Positioning System (GPS) as an efficient meteorological tool, GNSS data have been increasingly used for estimating atmospheric parameters, precipitable water vapor (Gendt et al, 2004; Luo et al, 2008; Jade and Vijayan, 2008; Bender et al, 2008; Alshawaf et al, 2015).
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