The evolution of citizen weather stations in urban climate research: A bibliometric analysis

Citizen weather stations have evolved from experimental curiosities into a critical source of high-resolution environmental intelligence. This review presents a comprehensive bibliometric and thematic analysis of the field's development from its inception in 2011 through October 2025. By analysing a corpus of 127 peer-reviewed articles across 67 journals, a trajectory of exponential growth is identified, with publication output increasing at an annual rate of 21.9%. Geographically, production is highly concentrated, with Germany, the Netherlands, and the UK accounting for the majority of institutional output. The analysis reveals that the field has progressed through four distinct evolutionary phases: a fragmented “Prototype Era” (pre-2019), a pivotal “Foundational Shift” (2019–2021) where data quality control emerged as the dominant enabler of trust, a rapid “Application Expansion” (post-2021) centred on Urban Heat Island intensity and Local Climate Zones, and a current “Rise of Frontiers” (2022-present) characterized by machine learning integration and multi-parameter sensing (rainfall and wind). The review concludes by identifying five strategic priorities: the next generation of ML-based quality control methods, novel data-generation techniques, eliminate socioeconomic placement bias, deeper operational and interdisciplinary integration, and standardizing global data access to unlock the potential of CWS for equitable urban climate adaptation. • Citizen weather data research grows 22% yearly since 2011. • Data quality controls now enable trusted urban heat studies. • Research progressed through four phases, from prototypes to machine learning. • Work increasingly targets urban heat patterns at city and neighbourhood scales. • Future needs include bias correction and more standardized data access.