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Lee Chapman and Simon J. Bell

Abstract

The impacts of weather and climate on infrastructure are numerous: snow and ice on roads, railway buckling, leaves on the line, wind impacts on power cabling, etc. Advances in modeling mean that these impacts can now be predicted at a high resolution so that mitigation activities can be targeted at vulnerable sections of the infrastructure network.

However, while high-resolution models have been in operational use for the last decade, in an environment of increasing litigation, practitioners remain nervous about making mitigation decisions solely based on model output. This means that the verification of forecasts is now needed on a scale previously not required, and it is only with this step that end users will become more open to using risk-based methods (e.g., decision support systems that enable selective salting for winter road maintenance where only the coldest sections of road are treated or localized rail speed restrictions in hot weather as opposed to the blanket restrictions currently used).

However, existing monitoring techniques are simply not capable of producing this information. Traditional in situ measurements are too expensive to install in the numbers required and therefore lack the spatial resolution. Conversely, mobile measurements lack the temporal resolution to provide the full picture. This paper outlines how the emerging Internet of Things is starting to provide the enabling technology to saturate our infrastructure with low-cost sensors. In doing so, it will provide unprecedented monitoring of weather impacts as well as facilitating a new generation of products harnessing the benefits of high-resolution observations.

Open access
Rick M. Thomas, A. Rob MacKenzie, S. James Reynolds, Jonathan P. Sadler, Ford Cropley, Simon Bell, Stephen J. Dugdale, Lee Chapman, Andrew Quinn, and Xiaoming Cai

Abstract

The increasing miniaturization of accurate, reliable meteorological sensors and logging systems allows the deployment of sensor packages on lightweight airborne platforms. Here, we demonstrate the safe and humane use of avian species (white-tailed and Spanish imperial eagles) to carry a prototype miniature sensor package to measure temperature with a 5-Hz response and ±0.2°C resolution. This technique could allow sensor deployment above complex urban terrain, where such data are urgently required. Recent meteorological work has been facilitated by using unmanned aerial vehicles (UAVs), but their use within, and adjacent to, urban areas is heavily controlled. The package contains a wind speed sensor, a GPS, a pressure altimeter, and accelerometers. Four flight tests were conducted in a steep valley (glen) at a remote Scottish location that provided contrasting vertical temperature profiles. The glen was instrumented with additional meteorological equipment at the bird launch and landing sites. Vertical temperature profile data from the raptors indicated the success of this approach with absolute temperatures and lapse rates consistent with those measured by the weather stations. Movement and airspeed data aided the interpretation of finescale temperature profiles in complex terrain. As well as the potential for meteorological sensing, this work is of interest to the avian ecology and behavior communities and to aerodynamicists interested in developing airborne robotics to mimic aspects of bird flight. These sensors are being miniaturized further for deployment on other bird species in urban areas for rapid, repeatable, and reliable measurements, with the potential to fulfill a measurement niche above the urban canopy.

Open access