In this master thesis the potential of GNSS-based tropospheric parameters for the forecast of regional precipitation events is investigated. A regional GNSS reference station network (operated by EPOSA, EVN and EAG) is used to extract relevant parameters, such as tropospheric zenith delays and tropospheric gradients. In order to obtain zenith wet delays (ZWD) from zenith total delays meteorological data from ZAMG are used. The following characteristic features can be anticipated in ZWD and gradient time series in case of precipitation events. First, an asymmetry in tropospheric delays induced by approaching weather fronts leads to increased gradient values. Furthermore, the direction of the gradients will point towards the weather front. Second, the increasing water vapor concentration right before a precipitation event results in larger ZWD values. After the event the ZWD will consequently diminish again. As a reference for these precipitation events weather data from ZAMG are used. Two test areas within Austria were specified to be analyzed. The investigations cover a time period of six months, starting with April 2014. To derive relevant information for predicting precipitation events exemplary test events are processed. On the one hand, the order of the anticipated increase in ZWD at each GNSS station within the test area indicates the direction of the approaching weather front. Therefore, ZWD time series are cross correlated. The resulting time delays provide the requested information. On the other hand, gradient time series are scanned to locate the increased absolute value induced by the approaching weather front, which allows the deduction of the direction of movement as well. Furthermore, for purposes of comparison the epoch of starting precipitation at each GNSS station is calculated. The order of ZWD increase almost matches the sequence of incipient precipitation. The directions of the gradients roughly agree as well. Using the weather data from ZAMG for verification it can be observed, that ZWD time series rather indicate the orientation of the air mass boundary and gradients rather indicate the direction of movement of an approaching weather front. Additionally, using tropospheric gradients for weather prediction allows a first indication of precipitation events well in advance. Thus, it can be concluded that the utilization of GNSS tropospheric parameters would improve weather forecasting models substantially.