## 1 Introduction  
The important role of water vapor in the hydrological cycle as well as in climate as the most effective greenhouse gas has been presented in numerous studies on weather and climate [1, 2]. Also, the major role and fast feedback processes of water vapor in a changing climate have been acknowledged for quite some time, yet large uncertainties exist in its variability and changes along with corresponding estimates of radiative forcing and climate sensitivity [3, 4, 5]. Many aspects of these studies, e.g., gaining improved understanding and model representation of the interaction of water vapor with other variables such as clouds and radiation, depend on accurate, comprehensive water vapor data sets [6, 7, 8]Longest homogeneous time series of water vapor exist from in situ radiosondes, e.g., [PERSON] et al. [9], though their temporal and spatial distribution is low. Satellite-based data now reach back more than 30 years, but first climatologies are limited to ocean surfaces [10]. Many more water vapor data sets from ground and spaceborne remote sensing exist. To make optimal use of various sources, reanalyses combine diverse measurements with numerical models, but herein, especially in data sparse regions, water vapor information relies on the underlying model leading to large differences between different reanalyses [11]. In the frame of obtaining an overview and assessing the quality of a wide range of available satellite-based water vapor datasets, the Global Energy and Water cycle Exchanges (GEWEX, Chahine [12]) Data and Assessments Panel (GDAP) has initiated the GEWEX Water Vapor Assessment (G-VAP) in 2011. It has the major purpose to quantify the current state of the art in water vapor products being constructed for climate applications, i.a. total column water vapor (TCWV), by the analyses and intercomparison of long-term satellite data records, including also data records from in situ and ground-based observations as well as from reanalyses [13]. Obviously, each of the above-mentioned individual sources of observational water vapor data have certain limitations. With respect to sampling and coverage, radiosondes and ground-based instruments provide water vapor observation on a local basis, are often limited to land areas and still very much concentrated in Northern-America and Europe. Observations from geostationary satellites are provided on high temporal resolution and on a large spatial scale, but do not cover the whole globe and currently are limited in their spectral capabilities in respect to moisture sensing. In contrast, observations from polar-orbiting satellites can be provided on a near-global scale each day. Polar platforms include hyper-spectral and microwave sounders, which are powerful for water vapor sounding, but have coarse spatial resolutions. Passive instruments on polar-orbiting satellites can provide accurate integrated water vapor (IWV, equal to TCWV) observations on a high spatial resolution up to 300 m, allowing observation of small-scale structures in the water vapor field [14], potentially very useful for research related to weather forecasts. Moreover, due to the daily global coverage of these satellite instruments and their, often, long-term measurements, corresponding IWV products provide large sample sizes and allows the production of global IWV climatologies. This makes them particularly suited for climate studies and model evaluations. However, the few daily overpass times for polar-orbiting satellites and the specifications of onboard instruments may lead to sampling biases in climatological IWV products, which need to be well characterized for accurate interpretations in climate studies. For example, [PERSON] and [PERSON] [15] found a positive bias for zonal means of IWV when comparing satellite water vapor data sets from passive microwave observations under all sky conditions with IWV under clear-sky conditions only, which was considered in the assessment of longwave cloud radiative forcing due to water vapor changes. [PERSON] et al.