Understory is creating a revolutionary type of data from its ground-truth network of proprietary weather sensors called RTis (real-time instruments). These sensors deliver roof-level measurements of hail and wind impacts. This is crucial information for groups that need to monitor property and infrastructure damage. Current systems do a poor job of tracking and predicting where severe thunderstorm damage occurred. We are reliant on radar estimates and spotter reports to identify damaged areas. The current stations in the Automated Surface Observing System (ASOS) network are unable to detect and report on hail, one of the main perils in supercell storms. Spotter reports only provide size estimates of hail, but the damage potential of a hailstorm is dependent on the velocity, composition, impact angle, and number of hailstones. Understory Weather manufactures and installs weather stations that measures the force and direction of every single hailstone that hits it. To ensure that hailstones are not missed, the stations take samples at over 3kHz, providing a high temporal resolution to use while reconstructing a storm's progress. The stations also measure wind, temperature, humidity, rain, and pressure. By measuring the force that is applied to the station by hail and wind with such high temporal resolution, the stations are able to construct a much more accurate picture of the damaging power of a given storm.
Understory Weather has sensor networks in Kansas City, Dallas, Denver, and St. Louis, covering the highest population centers of these metro areas with stations spaced every one to five kilometers. By blanketing a metro area with these stations, we can get a better measurement of how mesoscale systems affect a city, accurately determine where hail fell, and assess the potential damage from the storm. Data from the micronets is combined in real-time, providing a current picture of the conditions in those metro areas. Due to the density of the micronets, clear and accurate geospatial information can be assembled in real-time. Most mesonets are too widely spaced to capture the erratic fall of hail during storms and even to capture the spatial granularity of winds at surface levels. Deployed much more densely, micronets can contribute a necessary data layer for catastrophe and response planning. The potential applications of micronet data is vast, ranging from rapid response of emergency personnel, to more effective staging of insurance catastrophe response teams, to short-term wind forecasting for utility outages. In addition to catastrophe response, the localized weather data enables location-specific communication that allows the recipient to take action that is directly pertinent to their situation. Previous technologies were not accurate enough to provide a similar level of communication as Understory’s micronets.