A Demonstration of Low-Cost Observations in the Face of Adversity

Real-time or near-real-time meteorological information is necessary to support the decisions of forecasters, emergency management, and other governing bodies that affect life and property on a daily basis. Too often, the entities responsible for making such critical decisions lack the observational networks required to obtain this information because the financial barrier to acquiring professional-grade weather-observing systems is too great. The issue is compounded by the fact that parts of the world most adversely affected by weather are generally the most ill-equipped to address it. In response, USAID has sponsored the development of 3D-Printed Automatic Weather Stations (3D-PAWS) in order to meet the needs of developing communities around the world. These data are most important when the potential impact is large. During extreme events, weather information must be reliable and accurate. In Barbados, 3D-PAWS is put to the test by way of a volcanic eruption from La Soufrière and the subsequent ash fallout over the island in April of 2021. The dense network of nearly 100 stations captures associated changes in temperature and incoming solar radiation and will be evaluated for its ability to maintain continuous operation during extreme conditions when it matters most, thereby demonstrating an irreplaceable value on continuous, reliable, and low-cost networks of sensors when natural disasters strike.