Realizing the Potential of Vehicle-Based Observations

Mahoney, William P.

doi:10.1175/bams-d-12-00044

Cited by 6 publications

(7 citation statements)

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“…One of the most mature versions of a moving platform, in terms of crowdsourcing, research and exploration, are road vehicles. Commercial, public and personal road vehicles are beginning to contain Internet-connected sensors and have the potential to make high-resolution surface observations Mahoney and O'Sullivan, 2013), with research exploring data collected from such road vehicles already being undertaken. For example, Inrix (http://www.inrix.com/) collects data from trucks and other fleets as a source of real-time information about congestion and other issues affecting travel, while the Research and Innovative Technology Administration's (RITA) connected vehicle research initiative is encouraging the use of data from vehicle sensors (e.g.…”

Section: Moving Platformsmentioning

confidence: 99%

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

Muller

Chapman

Johnston³

et al. 2015

Intl Journal of Climatology

298

259

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Crowdsourcing is traditionally defined as obtaining data or information by enlisting the services of a (potentially large) number of people. However, due to recent innovations, this definition can now be expanded to include ‘and/or from a range of public sensors, typically connected via the Internet.’ A large and increasing amount of data is now being obtained from a huge variety of non‐traditional sources – from smart phone sensors to amateur weather stations to canvassing members of the public. Some disciplines (e.g. astrophysics, ecology) are already utilizing crowdsourcing techniques (e.g. citizen science initiatives, web 2.0 technology, low‐cost sensors), and while its value within the climate and atmospheric science disciplines is still relatively unexplored, it is beginning to show promise. However, important questions remain; this paper introduces and explores the wide‐range of current and prospective methods to crowdsource atmospheric data, investigates the quality of such data and examines its potential applications in the context of weather, climate and society. It is clear that crowdsourcing is already a valuable tool for engaging the public, and if appropriate validation and quality control procedures are adopted and implemented, it has much potential to provide a valuable source of high temporal and spatial resolution, real‐time data, especially in regions where few observations currently exist, thereby adding value to science, technology and society.

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Section: Moving Platformsmentioning

confidence: 99%

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

Muller

Chapman

Johnston³

et al. 2015

Intl Journal of Climatology

298

259

View full text Add to dashboard Cite

show abstract

“…For example, as part of a comprehensive review on the use of the technique in the atmospheric sciences, Muller et al (2015) discusses how the term has moved on from just sourcing services from the public to utilizing sensors via internet platforms to gather meteorological data or information. Examples of studies in the discipline include collecting air temperatures from smartphones (Overeem et al, 2013), temperature and precipitation data from vehicles (Mahoney and O'Sullivan, 2013) as well as supplementing traditional networks with amateur weather stations (Bell et al, 2013) and other smart devices.…”

Section: Crowdsourcingmentioning

confidence: 99%

Can the crowdsourcing data paradigm take atmospheric science to a new level? A case study of the urban heat island of London quantified using Netatmo weather stations

Chapman

Bell

2016

Intl Journal of Climatology

137

115

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Crowdsourcing techniques are frequently used across science to supplement traditional means of data collection. Although atmospheric science has so far been slow to harness the technology, developments have now reached the point where the benefits of the approaches simply cannot be ignored: crowdsourcing has potentially far‐reaching consequences for the way in which measurements are collected and used in the discipline. To illustrate this point, this paper uses air temperature data from the prolific, low‐cost, Netatmo weather station to quantify the urban heat island of London over the summer of 2015. The results are broadly comparable with previous studies, and indeed standard observations (albeit with a warm bias, a likely consequence of non‐standard site exposure), showing a range of magnitudes of between 1 and 6 °C across the city depending on atmospheric stability. However, not all the results can be easily explained by physical processes and therefore highlight quality issues with crowdsourced data that need to be resolved. This paper aims to kickstart a step‐change in the use of crowdsourcing in urban meteorology by encouraging atmospheric scientists to more positively engage with the new generation of manufacturers producing mass market sensors.

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“…The future of observational networks were discussed, specifically the networks which are not being designed or run specifically for meteorological applications. For example, important meteorological data is being extracted from existing networks such as AMDAR (AMDAR, ) and mode‐S data (de Haan, , de Haan and Stoffelen, , Strajnar, ) from air traffic, humidity measurements from global positioning systems (de Haan, ) and road traffic data (Mahoney and O'Sullivan, ). Increasingly, cheap sensors found in mobile phones are being adapted for use in all kinds of observational networks.…”

Section: Discussionmentioning

confidence: 99%

“…Ad hoc networks of devices such as smart phones and vehicles have exploded in size and functionality. These networks are currently being considered for their feasibility to provide information to assimilate into meteorological models (Mahoney and O'Sullivan, ). These networks have the potential to provide surface measurements at the resolutions required by future high resolution data assimilation systems, however they will still lack the three‐dimensional structure desired to fill the aforementioned observation gap.…”

Section: Current State Of Data Assimilation and Forecasting At High Rmentioning

confidence: 99%

RMetS Special Interest Group Meeting: high resolution data assimilation

Browne

Charlton‐Perez

Dance

2014

Atmospheric Science Letters

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Data assimilation (DA) systems are evolving to meet the demands of convection‐permitting models in the field of weather forecasting. On 19 April 2013 a special interest group meeting of the Royal Meteorological Society brought together UK researchers looking at different aspects of the data assimilation problem at high resolution, from theory to applications, and researchers creating our future high resolution observational networks. The meeting was chaired by Dr Sarah Dance of the University of Reading and Dr Cristina Charlton‐Perez from the MetOffice@Reading. The purpose of the meeting was to help define the current state of high resolution data assimilation in the UK. The workshop assembled three main types of scientists: observational network specialists, operational numerical weather prediction researchers and those developing the fundamental mathematical theory behind data assimilation and the underlying models. These three working areas are intrinsically linked; therefore, a holistic view must be taken when discussing the potential to make advances in high resolution data assimilation.

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Realizing the Potential of Vehicle-Based Observations

Cited by 6 publications

References 0 publications

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

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

Can the crowdsourcing data paradigm take atmospheric science to a new level? A case study of the urban heat island of London quantified using Netatmo weather stations

RMetS Special Interest Group Meeting: high resolution data assimilation

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