Global Spatiotemporal Variability of Integrated Water Vapor Derived from GPS, GOME/SCIAMACHY and ERA-Interim: Annual Cycle, Frequency Distribution and Linear Trends

Abstract

Atmospheric water vapor plays a prominent role in climate change and atmospheric, meteorological, and hydrological processes. Because of its high spatiotemporal variability, precise quantification of water vapor is challenging. This study investigates Integrated Water Vapor (IWV) variability for the period 1995–2010 at 118 globally distributed Global Positioning System (GPS) sites, using additional UV/VIS satellite retrievals by GOME, SCIAMACHY, and GOME-2 (denoted as GOMESCIA below), plus ERA-Interim reanalysis output. Apart from spatial representativeness differences, particularly at coastal and island sites, all three IWV datasets correlate well with the lowest mean correlation coefficient of 0.878 (averaged over all the sites) between GPS and GOMESCIA. We confirm the dominance of standard lognormal distribution of the IWV time series, which can be explained by the combination of a lower mode (dry season characterized by a standard lognormal distribution with a low median value) and an upper mode (wet season characterized by a reverse lognormal distribution with high median value) in European, Western American, and subtropical sites. Despite the relatively short length of the time series, we found a good consistency in the sign of the continental IWV trends, not only between the different datasets, but also compared to temperature and precipitation trends.

Observation of an Extremely Dry Atmospheric Air Column above Bern

“…Water vapour column density or vertically integrated water vapour (IWV) are monitored by various measuring instruments such as ground-based receivers of the Global Navigation Satellite System (GNSS), radiosondes, microwave radiometers, or Fourier transform infrared (FTIR) spectrometers [2]. Various studies indicated that IWV increased by several percents per decade, and this positive trend of IWV conforms with the expected increase of the water vapour abundance due to the increase of the air temperature as a consequence of man-made global warming [2][3][4][5][6]. According to the Clausius-Clapeyron relationship, a warmer atmosphere is associated with an amplification of the water vapour abundance.…”

Reproducing High Spatiotemporal Resolution Precipitable Water Distributions Using Numerical Prediction Data

“…Currently, methods commonly used to observe PW amounts include radiosonde observations [10], microwave radiometers [11,12], global navigation satellite system (GNSS) [13][14][15], and satellite remote sensing [16][17][18][19]. Of these, radiosonde observations are the traditional observation method [20].…”

Editorial for the Special Issue ″Climate Modelling and Monitoring Using GNSS″

“…Those papers can be arranged in major groups. Several papers [1][2][3] discuss different aspects in dealing with the estimation of long-term GNSS-derived water vapor trends and intercomparisons with external sources and NWP models. Other papers [4] use GNSS-estimated tropospheric parameters to evaluate NWP models and use these parameters for building ZTD climatological [5][6][7] or precipitation [8,9] models.…”