In recent years, personal weather stations (PWSs), which are low-cost citizen-installed devices, have emerged as a promising supplementary data source. These stations provide real-time high-resolution meteorological data and are proliferating globally through various commercial and volunteer-based networks. This review examines the role of PWSs in hydrology and meteorology, highlighting their potential for enhancing urban studies, flood modelling, and even numerical weather prediction. In this article, we provide an overview of major PWS networks and platforms, discuss recent applications, and explore methods for quality control and bias correction. We also present current approaches to quality assurance, describe methods for integration with official networks and remote sensing products, and outline emerging research directions. Emphasis is placed on the need for standardized benchmarking datasets, collaborative frameworks between institutions and citizen scientists, and ethical data governance.

Personal weather stations in hydrology and meteorology: a review of applications, challenges and future directions / Mazzoglio, P., Moccia, B., Ghaffaripour, E.. - In: HYDROLOGICAL SCIENCES JOURNAL. - ISSN 0262-6667. - ELETTRONICO. - (2026), pp. 1-17. [10.1080/02626667.2026.2665735]

Personal weather stations in hydrology and meteorology: a review of applications, challenges and future directions

Mazzoglio, Paola;
2026

Abstract

In recent years, personal weather stations (PWSs), which are low-cost citizen-installed devices, have emerged as a promising supplementary data source. These stations provide real-time high-resolution meteorological data and are proliferating globally through various commercial and volunteer-based networks. This review examines the role of PWSs in hydrology and meteorology, highlighting their potential for enhancing urban studies, flood modelling, and even numerical weather prediction. In this article, we provide an overview of major PWS networks and platforms, discuss recent applications, and explore methods for quality control and bias correction. We also present current approaches to quality assurance, describe methods for integration with official networks and remote sensing products, and outline emerging research directions. Emphasis is placed on the need for standardized benchmarking datasets, collaborative frameworks between institutions and citizen scientists, and ethical data governance.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/3012289