How close are opportunistic rainfall observations to providing societal benefit?

Olsson, Jonas (avtor), Horváth-Varga, Laura (avtor), Van de Beek, Remco (avtor), Graf, Maximilian (avtor), Overeem, Aart (avtor), Szaton, Magdalena (avtor), Bareš, Vojtěch (avtor), Bezak, Nejc (avtor), Chwala, Christian (avtor), De Michele, Carlo (avtor), Fencl, Martin (avtor), Seidel, Jochen (avtor), Todorović, Andrijana (avtor)

Mitigation of water-related hazards as well as sustainable water resources management are conditioned on accurate and detailed spatio-temporal rainfall observations. Today, water authorities like National Meteorological and Hydrological Services (NHMS) in developed countries operate observation systems consisting of meteorological stations and weather radars. These observations provide state-of-the-art precipitation products, but they remain error prone due to device-specific limitations. This has driven growing interest in opportunistic sensors (OS) of rainfall, primarily Commercial Microwave Links (CML) and Personal Weather Stations (PWS). In the Global South, where meteorological station networks are usually very sparse, OS rainfall data conceivably has an even higher potential to provide an added value. However, although numerous studies have demonstrated the capability and potential of accurate rainfall estimation by OS, no dedicated investigation has been made with regard to their application for operational monitoring and prediction. How close are OS rainfall data to providing societal benefit, e.g. by widespread integration in existing hydro-meteorological observation and prediction systems? We address this question by (1) making a review of studies that use OS rainfall data in applications (rainfall mapping, nowcasting and hydrological prediction), (2) providing a status report on the transition from research to operational usage from the perspective of EU COST Action OpenSense, and (3) discussing the challenges NHMS face in deploying OS rainfall data in operational services. We conclude that while distinct challenges still remain, in terms of both access and processing, the applicability of OS rainfall data is well scientifically supported and operation is underway in several countries.

• Jezik: Angleški jezik
• Ključne besede: rainfall data, opportunistic sensor, review study, hydrological prediction
• Vrsta gradiva: Članek v reviji
• Tipologija: 1.01 - Izvirni znanstveni članek
• Organizacija: FGG - Fakulteta za gradbeništvo in geodezijo
• Status publikacije: Objavljeno
• Različica publikacije: Recenzirani rokopis
• Leto izida: 2025
• Št. strani: Str. 1585-1602
• Številčenje: iss. 11, Letn. 26
• PID: 20.500.12556/RUL-176191
• UDK: 502/504:556
• ISSN pri članku: 1525-755X
• DOI: 10.1175/JHM-D-25-0043.1
• COBISS.SI-ID: 249021955
• Datum objave v RUL: 24.11.2025

Gradivo je del revije

• Naslov: Journal of hydrometeorology
• Skrajšan naslov: J. hydrometeorol.
• Založnik: American Meteorological Society
• ISSN: 1525-755X
• COBISS.SI-ID: 728341

Licence

• Licenca: CC BY 4.0, Creative Commons Priznanje avtorstva 4.0 Mednarodna
• Povezava: http://creativecommons.org/licenses/by/4.0/deed.sl
• Opis: To je standardna licenca Creative Commons, ki daje uporabnikom največ možnosti za nadaljnjo uporabo dela, pri čemer morajo navesti avtorja.

Sekundarni jezik

• Jezik: Slovenski jezik
• Ključne besede: podatki o padavinah, oportunistični senzorji, pregledna študija, hidrološke napovedi

Projekti

• Financer: SPARC project (project ID 2021-02380_Formas) funded by the Swedish Research Council Formas

• Financer: COST Action “Opportunistic Precipitation Sensing Network” CA20136, supported by European Cooperation in Science and Technology (COST)