What do we learn from long-term cloud condensation nuclei number concentration, particle number size distribution, and chemical composition measurements at regionally representative observatories?

Abstract. Aerosol-cloud interactions (ACI) constitute the single largest uncertainty in anthropogenic radiative forcing. To reduce the uncertainties and gain more confidence in the simulation of ACI, models need to be evaluated against observations, in particular against measurements of cloud condensation nuclei (CCN). Numerous observations of CCN number concentration exist, and many closure studies have been performed to predict CCN number concentrations based on particle number size distributions, chemical composition, and the κ-Köhler theory. Most of these studies provide details for short... Mehr ...

Verfasser: Bas Henzing
Roman Fröhlich
Ulrich Pöschl
Pasi Aalto
Minsu Park
Joel Brito
Urs Baltensperger
Hartmut Herrmann
Erik Herrmann
Mikael Ehn
Arnoud Frumau
Rupert Holzinger
Meintrat O. Andreae
Martin Gysel
Atsushi Matsuki
Nikolaos Mihalopoulos
Nikos Kalivitis
Tuukka Petäjä
Erik Swietlicki
Adam Kristensson
Laurent Poulain
Göran Frank
John A. Ogren
Alfred Wiedensohler
Frank Stratmann
Samara Carbone
David Picard
Gerard Kos
Mira L. Pöhlker
André S. H. Prévôt
Julia Schmale
Paulo Artaxo
Aikaterini Bougiatioti
Christopher Pöhlker
Mikhail Paramonov
Helmi Keskinen
Colin D. O'Dowd
Nicolas Bukowiecki
Seong Soo Yum
Jurgita Ovadnevaite
Iasonas Stavroulas
Markku Kulmala
Anne Jefferson
Karine Sellegri
Mikko Äijälä
Stefano Decesari
Silvia Henning
Athanasios Nenes
Yoko Iwamoto
Patrick Schlag
Dokumenttyp: Artikel
Erscheinungsdatum: 2017
Schlagwörter: Research and Innovation action / Netherlands / EC / European Commission / Knowmad Institut / H2020
Sprache: unknown
Permalink: https://search.fid-benelux.de/Record/base-29597942
Datenquelle: BASE; Originalkatalog
Powered By: BASE
Link(s) : https://www.openaccessrepository.it/record/131003

Abstract. Aerosol-cloud interactions (ACI) constitute the single largest uncertainty in anthropogenic radiative forcing. To reduce the uncertainties and gain more confidence in the simulation of ACI, models need to be evaluated against observations, in particular against measurements of cloud condensation nuclei (CCN). Numerous observations of CCN number concentration exist, and many closure studies have been performed to predict CCN number concentrations based on particle number size distributions, chemical composition, and the κ-Köhler theory. Most of these studies provide details for short time periods or focus on special environmental conditions. These observations, however, cannot address questions of large-scale temporal and spatial CCN variability. Here we analyze long-term observations of CCN number concentrations, particle number size distributions and chemical composition from twelve sites on three continents. Eight of these stations are part of the European Aerosols, Clouds, and Trace gases Research InfraStructure (ACTRIS). We group the observatories into categories according to their official classification: coastal background (Barrow, Alaska; Mace Head, Ireland; Finokalia, Crete; Noto Peninsula, Japan), rural background (Melpitz, Germany; Cabauw, the Netherlands; Vavihill, Sweden), alpine sites (Puy de Dôme, France; Jungfraujoch, Switzerland), remote forest sites (ATTO, Brazil; SMEAR, Finland) and the urban environment (Seoul, South Korea). Expectedly, CCN characteristics are highly variable across regions. However, they also vary within categories, most strongly in the coastal background group, where CCN number concentrations can vary by up to a factor of 30 within one season. In terms of particle activation behavior, most continental stations exhibit very similar relative activation ratios across the range of 0.1 to 1.0 % supersaturation. At the coastal sites the activation ratios spread more widely across the SS spectrum. Several stations show strong seasonal cycles of CCN number concentrations ...