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New trajectory-driven aerosol and chemical process model Chemical and Aerosol Lagrangian Model (CALM)
Stockholm University, Faculty of Science, Department of Applied Environmental Science (ITM).
Stockholm University, Faculty of Science, Department of Applied Environmental Science (ITM).
2010 (English)In: Atmospheric Chemistry And Physics, ISSN 1680-7316, E-ISSN 1680-7324, Vol. 10, no 21, p. 10161-10185Article in journal (Refereed) Published
Abstract [en]

A new Chemical and Aerosol Lagrangian Model (CALM) has been developed and tested. The model incorporates all central aerosol dynamical processes, from nucleation, condensation, coagulation and deposition to cloud formation and in-cloud processing. The model is tested and evaluated against observations performed at the SMEAR II station located at Hyytiala (61 degrees 51'N, 24 degrees 17'E) over a time period of two years, 2000-2001. The model shows good agreement with measurements throughout most of the year, but fails in reproducing the aerosol properties during the winter season, resulting in poor agreement between model and measurements especially during December-January. Nevertheless, through the rest of the year both trends and magnitude of modal concentrations show good agreement with observation, as do the monthly average size distribution properties. The model is also shown to capture individual nucleation events to a certain degree. This indicates that nucleation largely is controlled by the availability of nucleating material (as prescribed by the [H2SO4]), availability of condensing material (in this model 15% of primary reactions of monoterpenes (MT) are assumed to produce low volatile species) and the properties of the size distribution (more specifically, the condensation sink). This is further demonstrated by the fact that the model captures the annual trend in nuclei mode concentration. The model is also used, alongside sensitivity tests, to examine which processes dominate the aerosol size distribution physical properties. It is shown, in agreement with previous studies, that nucleation governs the number concentration during transport from clean areas. It is also shown that primary number emissions almost exclusively govern the CN concentration when air from Central Europe is advected north over Scandinavia. We also show that biogenic emissions have a large influence on the amount of potential CCN observed over the boreal region, as shown by the agreement between observations and modeled results for the receptor SMEAR II, Hyytiala, during the studied period.

Place, publisher, year, edition, pages
2010. Vol. 10, no 21, p. 10161-10185
National Category
Earth and Related Environmental Sciences
Research subject
Applied Environmental Science
Identifiers
URN: urn:nbn:se:su:diva-51326DOI: 10.5194/acp-10-10161-2010ISI: 000284210400002OAI: oai:DiVA.org:su-51326DiVA, id: diva2:385068
Note
authorCount :3Available from: 2011-01-11 Created: 2011-01-10 Last updated: 2022-02-24Bibliographically approved
In thesis
1. Inverse Modeling of Cloud – Aerosol Interactions
Open this publication in new window or tab >>Inverse Modeling of Cloud – Aerosol Interactions
2011 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

The role of aerosols and clouds is one of the largest sources of uncertainty in understanding climate change. The primary scientific goal of this thesis is to improve the understanding of cloud-aerosol interactions by applying inverse modeling using Markov Chain Monte Carlo (MCMC) simulation.

Through a set of synthetic tests using a pseudo-adiabatic cloud parcel model, it is shown that a self adaptive MCMC algorithm can efficiently find the correct optimal values of meteorological and aerosol physiochemical parameters for a specified droplet size distribution and determine the global sensitivity of these parameters. For an updraft velocity of 0.3 m s-1, a shift towards an increase in the relative importance of chemistry compared to the accumulation mode number concentration is shown to exist somewhere between marine (~75 cm-3) and rural continental (~450 cm-3) aerosol regimes.

Examination of in-situ measurements from the Marine Stratus/Stratocumulus Experiment (MASE II) shows that for air masses with higher number concentrations of accumulation mode (Dp = 60-120 nm) particles (~450 cm-3), an accurate simulation of the measured droplet size distribution requires an accurate representation of the particle chemistry. The chemistry is relatively more important than the accumulation mode particle number concentration, and similar in importance to the particle mean radius. This result is somewhat at odds with current theory that suggests chemistry can be ignored in all except for the most polluted environments. Under anthropogenic influence, we must consider particle chemistry also in marine environments that may be deemed relatively clean.

The MCMC algorithm can successfully reproduce the observed marine stratocumulus droplet size distributions. However, optimising towards the broadness of the measured droplet size distribution resulted in a discrepancy between the updraft velocity, and mean radius/geometric standard deviation of the accumulation mode. This suggests that we are missing a dynamical process in the pseudo-adiabatic cloud parcel model.  

Place, publisher, year, edition, pages
Stockholm: Department of Applied Environmental Science (ITM), Stockholm University, 2011. p. 64
Keywords
stratocumulus, marine, cloud, aerosol, interactions, MCMC, inverse modeling, droplet closure, global sensitivity
National Category
Meteorology and Atmospheric Sciences
Research subject
Applied Environmental Science
Identifiers
urn:nbn:se:su:diva-60454 (URN)978-91-7447-343-8 (ISBN)
Public defence
2011-09-23, Nordenskiöldsalen, Geovetenskapens hus, Svante Arrhenius väg 12, Stockholm, 13:00 (English)
Opponent
Supervisors
Note
At the time of the doctoral defense, the following papers were unpublished and had a status as follows: Paper 3: Submitted. Paper 4: Manuscript.Available from: 2011-09-01 Created: 2011-08-17 Last updated: 2022-02-24Bibliographically approved

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Tunved, PeterPartridge, David G.

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