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.

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.

Annual, monthly, and daily analyses of stable isotopes in precipitation are commonly made worldwide, yet only a few studies have explored the variations occurring on short time scales within individual precipitation events, particularly at midlatitude locations. This study examines hydrogen isotope data from sequential, intra-event samples from 16 precipitation events during different seasons and a range of synoptic conditions over an 18-month period in Birmingham, United Kingdom. Precipitation events were observed simultaneously using a vertically pointing micro rain radar (MRR), which, for the first time at a midlatitude location, allowed high-resolution examination of the microphysical characteristics (e.g., rain rate, fall velocity, and drop size distributions) that may influence the local isotopic composition of rainwater. The range in the hydrogen isotope ratio (δD, where D refers to deuterium) in 242 samples during 16 events was from −87.0‰ to +9.2‰, while the largest variation observed in a single event was 55.4‰. In contrast to previous work, the results indicate that some midlatitude precipitation events do indeed show significant intra-event trends that are strongly influenced by precipitation processes and parameters such as rain rate, melting-level height, and droplet sizes. Inverse relationships between rain rate and isotopic composition are observed, representing an example of a local type of “amount effect,” a still poorly understood process occurring at different scales. For these particular events, the mean δ value may therefore not provide all the relevant information. This work has significance for the testing and development of isotope-enabled cloud-resolving models and land surface models at higher resolutions, and it provides improved insights into a range of environmental processes that are influenced by subsampled precipitation events.

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 of spatiotemporal patterns of temperature for agricultural and urban meteorological phenomena such as the urban heat island. With the launch of a new generation of low-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$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, notably urban areas. Assessment of the performance of the ASM relative to traceable standards in a water bath and atmospheric chamber show it to have good measurement accuracy with mean errors <±0.22°C between −25° and 30°C, with a time constant in ambient air of 110 ±15 s. Subsequent field tests also showed the ASM (in the custom shield) had excellent performance (RMSE = 0.13°C) 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.