SMEARcore – modular data infrastructure for atmospheric measurement stations

Abstract We present the SMEARcore data infrastructure framework: a collection of modular programs and processing workflows intended for measurement stations and campaigns as a real-time data analysis and management platform. SMEARcore enables new SMEAR (Station for Measuring Ecosystem–Atmosphere Relations) stations to be integrated in a way that is consistent with existing stations and transfers the existing data curation experience to the new station. It establishes robust data pipelines that allow easier diagnosis of problems. We show practical examples of how SMEARcore is utilized at operational measurement stations. This work differs from earlier similar concepts, such as those used at stations within ACTRIS (Aerosols, Clouds and Trace Gases Research Infrastructure) and ICOS (Integrated Carbon Observation System) networks, in three important aspects: firstly, by keeping all the processing under the control of the data owners; secondly, by providing tools for making data interoperable in general instead of harmonizing a particular set of instruments; and thirdly, by being extensible to new instruments. As such it is not meant as a replacement for these infrastructures but to be used in addition to them and to bring structured data curation to more measurement stations not yet using these practices.

Object Details

• Location: Deutsche Nationalbibliothek Frankfurt am Main
• Extent: Online-Ressource
• Language: Englisch

References and Relationships

• Bibliographic citation: SMEARcore – modular data infrastructure for atmospheric measurement stations ; volume:16 ; number:11 ; year:2023 ; pages:2781-2793 ; extent:13 ; Atmospheric measurement techniques ; 16, Heft 11 (2023), 2781-2793 (gesamt 13)

Contributors, Places and Time

• Creator: Rusanen, Anton ; Hõrrak, Kristo ; Ahonen, Lauri R. ; Nieminen, Tuomo ; Aalto, Pasi P. ; Kolari, Pasi ; Kulmala, Markku ; Petäjä, Tuukka ; Junninen, Heikki

Further information

• DOI: 10.5194/amt-16-2781-2023
• URN: urn:nbn:de:101:1-2023060804291034541449
• Rights: Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
• Last update: 14.08.2025, 10:47 AM CEST