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Greenroofs are roof designs that incorporate plants and growing media above a water-proofing membrane. They are implemented to achieve a number of ecosystem services, especially stormwater management whereby the goal is to achieve the maximum amount of overall stormwater used or stored. The purpose of this study is to demonstrate how wireless sensor networks can gather the real-time data needed to assess the impact of storm events and efficiency of green roofs, to eventually maximize stormwater retention by greenroofs. In this paper, we present data from three intensively-sensored experimental greenroof platforms planted in either Sedum album, Sedum spurium, or left unplanted. Substrate moisture is monitored continuously at 5-minute intervals with 25 Echo-TM sensors, with ECRN-50 rain gauges measuring stormwater runoff in each platform. Environmental variables such as air and soil temperature, relative humidity, wind speed, photosynthetic and total solar radiation, and precipitation are also collected at the study site in real time. We show how this data can be used to validate model predictions about evapotranspiration and runoff from greenroofs. We compare the Hargreaves Samani and FAO Penman Monteith equations for estimating evapotranspiration with data collected from the platforms. Information from this comparison will be used in the future to create a mechanistic model of the greenroof water cycle. Only with a clear understanding of how much water greenroofs might retain for different climatic scenarios will managers be able to consider or refine policies regarding permitting and incentives for this type of roof construction.