A spatially high resolved total column water vapour (TCWV) dataset over land surfaces with uncertainty estimates for each pixel has been derived for the period January 2003 to March 2012 in frame of the ESA DUE GlobVapour project [Lindstrot et al., 2014]. It is based on near-infrared measurements of Medium Resolution Imaging Spectrometer (MERIS) onboard Environmental Satellite (ENVISAT). The dataset was already validated against radiosonde, ground-based microwave and GPS derived TCWV [Lindstrot et al., 2012]. Now, it is statistically analysed in order to identify trends within the previously mentioned time frame. Therefore, monthly composites on a rectangular longitude-latitude grid with a spatial resolution of 0.5 - 0.5 have been used in a multiple linear regression. Thereby, two different Ordinary Least-Square (OLS) models have been applied. One of them takes a possible lagged El-Nino Southern Oscillation (ENSO) influence into account while the other one disregards the link. Additionally, trend uncertainties have been estimated, whereby in presence of heteroskedasticity and/or autocorrelation the estimation is based on Newey-West standard errors. Subsequent hypothesis testing delivered spatially high resolved significant positive and negative regional trend patterns over land surfaces, such as an increase in water vapour for the east coast of Australia and a decrease for parts of Mexico. Finally, these patterns have been qualitatively compared to ERA-Interim Total Column Water Vapour (TCWV) trends, delivering similar and different regions of increasing and decreasing water vapour within the considered period and indicating a superior regional structure of the water vapour distribution within the MERIS TCWV data set.