E. J. S. Ferranti

The Birmingham Urban Climate Laboratory: an open meteorological test bed and challenges of the smart city

AbstractThe Birmingham Urban Climate Laboratory (BUCL) is a near-real-time, high-resolution urban meteorological network (UMN) of automatic weather stations and inexpensive, nonstandard air temperature sensors. The network has recently been implemented with an initial focus on monitoring urban heat, infrastructure, and health applications. A number of UMNs exist worldwide; however, BUCL is novel in its density, the low-cost nature of the sensors, and the use of proprietary Wi-Fi networks. This paper provides an overview of the logistical aspects of implementing a UMN test bed at such a density, including selecting appropriate urban sites; testing and calibrating low-cost, nonstandard equipment; implementing strict quality-assurance/quality-control mechanisms (including metadata); and utilizing preexisting Wi-Fi networks to transmit data. Also included are visualizations of data collected by the network, including data from the July 2013 U.K. heatwave as well as highlighting potential applications. The pap...

Heat-Related Failures on Southeast England’s Railway Network: Insights and Implications for Heat Risk Management

AbstractHigh temperatures and heat waves can cause numerous problems for railway infrastructure, such as track buckling, sagging of overhead lines, and the failure of electrical equipment. Without adaptation, these problems are set to increase in a future warmer climate. This study used industry fault data to examine the temporal and spatial distribution of heat-related incidents in southeast England and produce a unique evidence base of the impact of temperature on the rail network. In particular, the analysis explored the concept of failure harvesting, whereby the infrastructure system becomes increasingly resilient to temperature over the course of the summer season (April–September) as the most vulnerable assets fail with each incremental rise in temperature. The analysis supports the hypothesis and clearly shows that a greater number of heat-related incidents occur in the early/midsummer season before reducing significantly, despite equivalently high temperatures. This failure harvesting and the cons...

Using GIS to Investigate Spatial and Temporal Variations in Upland Rainfall

A method is presented for conditional analysis of spatial and temporal (1961–2007) variations in rainfall under different synoptic situations and different geographic sub-regions, using Cumbria in NW England as a study area. A daily synoptic typing scheme, the Lamb Weather Catalogue, was applied to identify rainfall under three different weather types: south-westerly (SW), westerly (W) and cyclonic (C). Topographic descriptors developed using GIS were used to classify rain gauges into six geographic sub-regions: coastal, windward-lowland, windward-upland, leeward-upland, leeward-lowland, secondary upland. Examining temporal rainfall trends associated with different weather types, in different geographic sub-regions, reveals useful information on changes in rainfall processes. The total rainfall under SW and W weather types is increasing, particularly in upland regions. The increase in SW rainfall is driven by more frequent wet-days, whereas the increase in W rainfall is driven by increases in both wet-day frequency and yield per wet-day. The rainfall under C weather types is decreasing. Combining GIS and synoptic climatology gives insights into rainfall processes under a changing climate. The conditional analysis method can be applied at both local and regional scales, and its success is largely due to the ability of GIS to integrate, visualise, and efficiently model spatial data.