Catherine L. Muller

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...

Towards a standardised metadata protocol for urban meteorological networks

With the growing number and significance of urban meteorological networks (UMNs) across the world, it is becoming critical to establish a standard metadata protocol. Indeed, a review of existing UMNs indicate large variations in the quality, quantity, and availability of metadata containing technical information (i.e., equipment, communication methods) and network practices (i.e., quality assurance/quality control and data management procedures). Without such metadata, the utility of UMNs is greatly compromised. There is a need to bring together the currently disparate sets of guidelines to ensure informed and well-documented future deployments. This should significantly improve the quality, and therefore the applicability, of the high-resolution data available from such networks. Here, the first metadata protocol for UMNs is proposed, drawing on current recommendations for urban climate stations and identified best practice in existing networks.

Quantifying the Daytime and Night-Time Urban Heat Island in Birmingham, UK: A Comparison of Satellite Derived Land Surface Temperature and High Resolution Air Temperature Observations

The Urban Heat Island (UHI) is one of the most well documented phenomena in urban climatology. Although a range of measurements and modelling techniques can be used to assess the UHI, the paucity of traditional meteorological observations in urban areas has been an ongoing limitation for studies. The availability of remote sensing data has therefore helped fill a scientific need by providing high resolution temperature data of our cities. However, satellite-mounted sensors measure land surface temperatures (LST) and not canopy air temperatures with the latter being the key parameter in UHI investigations. Fortunately, such data is becoming increasingly available via urban meteorological networks, which now provide an opportunity to quantify and compare surface and canopy UHI on an unprecedented scale. For the first time, this study uses high resolution air temperature data from the Birmingham Urban Climate Laboratory urban meteorological network and MODIS LST to quantify and identify the spatial pattern of the daytime and night-time UHI in Birmingham, UK (a city with an approximate population of 1 million). This analysis is performed under a range of atmospheric stability classes and investigates the relationship between surface and canopy UHI in the city. A significant finding of this work is that it demonstrates, using observations, that the distribution of the surface UHI appears to be clearly linked to landuse, whereas for canopy UHI, advective processes appear to play an increasingly important role. Strong relationships were found between air temperatures and LST during both the day and night at a neighbourhood scale, but even with the use of higher resolution urban meteorological datasets, relationships at the city scale are still limited.

A Low-Cost Wireless Temperature Sensor: Evaluation for Use in Environmental Monitoring Applications

A wide range of environmental applications would benefit from a dense network of air temperature observations. However, with limitations of costs, existing siting guidelines, and risk of damage, new methods are required to gain a high-resolution understanding ofspatiotemporal patterns oftemperature for agricultural and urbanmeteorologicalphenomenasuchastheurbanheatisland.Withthelaunchofanewgenerationoflow-cost sensors, it is possible to deploy a network to monitor air temperature at finer spatial resolutions. This study investigates the Aginova Sentinel Micro (ASM) sensor with a custom radiation shield (together less than USD

Debugging Geographers: Teaching Programming to Non-Computer Scientists.

150) that can provide secure near-real-time air temperature data to a server utilizing existing (or user deployed) Wi-Fi networks. This makes it ideally suited for deployment where wireless communications readily exist,notablyurbanareas.AssessmentoftheperformanceoftheASMrelativetotraceablestandardsinawater bath and atmospheric chamber show it to have good measurement accuracy with mean errors ,60.228 Cb etween 2258 and 308C, with a time constant in ambient air of 110 615s. Subsequent field tests also showed the ASM (in the custom shield) had excellent performance (RMSE 5 0.138C) over a range of meteorological conditions relative to a traceable operational Met Office platinum resistance thermometer. These results indicate that the ASM and radiation shield are more than fit for purpose for dense network deployment in environmental monitoring applications at relatively low cost compared to existing observation techniques.

The Birmingham Urban Climate Laboratory-A high density, urban meteorological dataset, from 2012-2014.

The steep learning curve associated with computer programming can be a daunting prospect, particularly for those not well aligned with this way of logical thinking. However, programming is a skill that is becoming increasingly important. Geography graduates entering careers in atmospheric science are one example of a particularly diverse group who often require a better knowledge and understanding of computing. Critically, there is a necessity in the field for people with a diverse range of data analysis and modelling abilities. This article outlines the module design and evaluation of an introductory programming course for non-computer scientists within a UK geography department.

The Combined Passive Microwave-Infrared (PMIR) Algorithm

There is a paucity of urban meteorological observations worldwide, hindering progress in understanding and mitigating urban meteorological hazards and extremes. High quality urban datasets are required to monitor the impacts of climatological events, whilst providing data for evaluation of numerical models. The Birmingham Urban Climate Laboratory was established as an exemplar network to meet this demand for urban canopy layer observations. It comprises of an array of 84 wireless air temperature sensors nested within a coarser array of 24 automatic weather stations, with observations available between June 2012 and December 2014. data routinely underwent quality control, follows the ISO 8601 naming format and benefits from extensive site metadata. The data have been used to investigate the structure of the urban heat island in Birmingham and its associated societal and infrastructural impacts. The network is now being repurposed into a testbed for the assessment of crowd-sourced and satellite data, but the original dataset is now available for further analysis, and an open invitation is extended for its academic use.

Crowdsourcing for climate and atmospheric sciences: current status and future potential

The retrieval of satellite rainfall estimates from multi-platform Earth observations has received much attention over the last decade. The Passive Microwave – InfraRed algorithm, developed at the University of Birmingham, has been operating in a quasi-operational mode since 2002. The algorithm combines the temporally-rich information from the infrared geostationary observations with the more quantitative, but less frequent, rainfall information from the passive microwave polar-orbiting satellites. Co-located infrared and passive microwave information is entered into a database which is used to generate the relationship between the surface rainfall and infrared cloud top temperatures at a centred-weighted 5舁×舁5 scale. The technique produces rainfall estimates at a temporal resolution of 30 min and a spatial resolution of 0.1舁×舁0.1: the user can then aggregate these results to suit their requirements.