Cloud condensation nuclei (CCN) number concentrations alongside with submicrometer particle number size distributions and particle chemical composition have been measured at atmospheric observatories of the Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS) as well as other international sites over multiple years. Here, harmonized data records from 11 observatories are summarized, spanning 98,677 instrument hours for CCN data, 157,880 for particle number size distributions, and 70,817 for chemical composition data. The observatories represent nine different environments, e.g., Arctic, Atlantic, Pacific and Mediterranean maritime, boreal forest, or high alpine atmospheric conditions. This is a unique collection of aerosol particle properties most relevant for studying aerosol-cloud interactions which constitute the largest uncertainty in anthropogenic radiative forcing of the climate. The dataset is appropriate for comprehensive aerosol characterization (e.g., closure studies of CCN), model-measurement intercomparison and satellite retrieval method evaluation, among others. Data have been acquired and processed following international recommendations for quality assurance and have undergone multiple stages of quality assessment.
|Publication status||Published - 2017 Mar 14|
Bibliographical noteFunding Information:
Long-term measurements at Jungfraujoch are supported by the International Foundation High Altitude Research Stations Jungfraujoch and Gornergrat and Meteo Swiss in the framework of the Global Atmosphere Watch (GAW) program. AN acknowledges support from a Georgia Power Faculty Scholar and a Cullen-Peck Faculty Fellow funds. JO thanks the HEA-PRTLI4 Environment and Climate: Impact and Responses programme and EPA-Ireland. The research at Cabauw has received funding from the European Union Seventh Framework Programme (FP7, grant agreement no. 262254). The research at Noto was supported by JSPS Grant-in-Aid for Young Scientists (A, grant number JP26701001). The research in Seoul was supported by Grant KMIPA 2015-2061.
© The Author(s) 2017.
All Science Journal Classification (ASJC) codes
- Statistics and Probability
- Information Systems
- Computer Science Applications
- Statistics, Probability and Uncertainty
- Library and Information Sciences