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

Abstract

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.

Crowdsourcing, Citizen Science or Volunteered Geographic Information? The Current State of Crowdsourced Geographic Information

“…Figure 6 aims only to provide a simple generalization of the situation. There are, for example, a wide variety of weather related citizen science projects which could occupy different locations in the space depicted in Figure 6; see for example, [56].…”

Crowdsourcing for agricultural applications: A review of uses and opportunities for a farmsourcing approach

“…Data quality is reported to increase with the number of contributions (e.g., as 442 cited in Muller et al, 2015), and it is even reported that high quality data can emerge from a vast 443 amount of low quality data (De Longueville, 2015). It does not mean that more contributions 444 automatically result in better quality outputs, but rather that more contributions allow for a stronger 445 quality check of the crowdsourced data.…”

“…458 However, crowdsourcing approaches based on more flexible data models have shown a greater 459 potential to 1) support unanticipated evolution of the crowdsourcing initiatives and 2) attract and 460 maintain a larger group of contributors (Lukyanenko et al, 2014 (Muller et al, 2015).…”

Capitalizing on Cellular Technology—Opportunities and Challenges for Near Ground Weather Monitoring

“…CML technology has recently been mentioned as one of the first Internet of Things (IoT) applications [85], which is now getting much attention. While the conditions for CML technology becoming useful seems to be right, and we may see it soon in products as well as in public-good services, it also serves as a pioneering example of the new trend of capitalizing on existing technology by utilizing it for non-intended, opportunistic use [86][87][88].…”