Atmospheric humidity strongly affects the economy of nature and has a cardinal part in a variety of environmental processes (e.g. Allan et al., 1999). As the most influential of greenhouse gases, it absorbs long-wave terrestrial radiation. Through the water vapour evaporation and recondensation cycle, it plays a central part in the Earth's energy redistribution mechanism by transferring heat energy from the surface to the atmosphere. Meteorological decision-support for weather forecasting is based on atmospheric model results, the accuracy of which is determined by the quality of its initial conditions or forcing data. Humidity, in particular, is a critical variable in the initialization of these models. The Mesoscale Alpine Programme (MAP) which set out to improve prediction of the regional weather, and specifically rainfall and flooding, concluded that accurate moisture fields for initialization were of great importance in achieving improved results (Ducrocq et al., 2002). Humidity measurements are predominantly obtained by either surface stations, radiosondes or satellite systems. The typical surface station instruments commonly provide only very local, point, observations, and therefore suffer from low spatial resolution. Moisture though, is a field with an unusually high variability in the mesoscale as demonstrated, for instance, by structure functions (Lilly & Gal-Chen, 1983). Compounding this problem is the limited accessibility to position humidity gauges in heterogeneous terrain, or areas with complex topography. Satellites allow for a large area to be covered, but are frequently not accurate enough in measuring surface level moisture while this near-surface moisture is, in most cases, the important variable for convection. Radiosondes, which are typically launched only 2-4 times a day, also provide very limited information. Additionally, these monitoring methods are costly for implementation, deployment and maintenance. Because of surface perturbation a point measurement close to the surface (for example 2m from the ground as in a standard meteorological surface station) is not satisfactory for model initialization. What is ideally required for meteorological modeling purposes is an area average measurement of near-surface moisture over a box with the scale of the model's grid and at an altitude of a few tens of meters. Current measuring tools cannot effectively provide this type of data. The method we present in this chapter provides a unique way of obtaining precisely this type of measurement. We introduce a technique, originally published by David et al. (2009), to measure atmospheric humidity using data collected by wireless communication networks.