Atmosphere Modelling Group

The atmosphere modelling group focuses their activities on the development of models that aim to study biosphere stress effects, its adaptation, biosphere-atmosphere exchange and aerosol formation involving coniferous and deciduous forest types for several stations in the boreal regions and worldwide covering different latitudes and ecosystems. Further we investigate the impacts of different aerosol loadings primary, and secondary, on the local and global climate and try to improve our understanding of in the cloud formation mechanisms which is still far away from complete. We aim at finding process parameterizations that can be subsequently applied in climate predictions and reduce significant uncertainties therein. The model activities are on different time-scales reaching from milliseconds in the cloud-process-studies to years in the global climate model and cover a wide spatial range from centimeters up to the globe. The strength of the group arises from a strong collaboration between the group members and in this manner also between the different models. A short description for each individual model and related references are presented below. More detailed information is available on request from Michael Boy (group leader).

• UHMA
• MALTE/MALTE-BOX
• SOSAA
• FLAMO
• PENCIL-CLOUD
• ECHAM

UHMA

Aerosol dynamical processes are being studied with the UHMA (University of Helsinki Multi-component Aerosol) model which was first published by Korhonen and co-workers in 2004. UHMA is a size segregated (hybrid sectional) box model, and includes all the basic aerosol dynamical processes in clear sky conditions: nucleation, coagulation, condensation and dry deposition. The model has been successful in modelling new particle formation events observed at the Hyytiälä measurement station (see Figures 1-2). The model is being developed actively and recently it has been rewritten into UHMAEMO, which is more easily extended and improves on several features.

Figure 1 and 2: Measured and modelled particle number concentrations with a new method to estimate the concentration of condensing organic vapours. More details under Vuollekoski, et al., 2010a.

Related publications from the group:

S.-L. Sihto, H. Vuollekoski, J. Leppä, I. Riipinen, V.-M. Kerminen, H. Korhonen, K. E. J. Lehtinen, M. Boy, and M. Kulmala: Aerosol dynamics simulations on the connection of sulphuric acid and new particle formation, Atmos. Chem. Phys., 9, 2933-2947, 2009.

E.-M. Kyrö, T. Grönholm, H. Vuollekoski, A. Virkkula, M. Kulmala and L. Laakso: Snow scavenging of ultrafine particles: field measurements and parameterization, Boreal. Env. Res., 14, 527-538, 2009.

H. Vuollekoski, V.-M. Kerminen, T. Anttila, S.-L. Sihto, M. Vana, M. Ehn, H. Korhonen, G. McFiggans, C. D. O’Dowd and M. Kulmala: Iodine dioxide nucleation simulations in coastal and remote marine environments, Journal of Geophys. Res., 114, D02206, 2009.

Vuollekoski, H., Boy, M., Kerminen, V.-M., Lehtinen, K.E.J. and Kulmala, M.: MECCO: A method to estimate concentrations of condensing organics – description and evaluation of a Markov chain Monte Carlo application, Journal of Aerosol Science 41, 1080-1089 , 2010a.

Vuollekoski, H., Nieminen, T., Paasonen, P., Sihto, S.-L., Boy, M., Manninen, H., Lehtinen, K., Kerminen, V.-M. and Kulmala, M.: Atmospheric nucleation and initial steps of particle growth: numerical comparison of different theories and hypotheses, Atmos. Research 98, 229-236, 2010b.

MALTE and MALTE-BOX

MALTE-BOX and MALTE (Model to predict new Aerosol formation in the Lower TropospherE) are a zero- and an one-dimensional model which include several modules for the simulation of boundary layer dynamics and both chemical and aerosol dynamical processes. The aerosol dynamics are solved by the size-segregated aerosol model UHMA, the emissions are predicted by MEGAN (Model for Emissions of Gases and Aerosols in Nature, Guenther et al., 2006) and gas phase chemistry is solved with the kinetic preprocessor (KPP) in combination with the Master Chemical Mechanism (MCM). The model was developed during the last six years at the University of Helsinki and the National Centre for Atmospheric Research in Boulder, Colorado, USA.

Figure 3: Observed and simulated particle number concentration N>10 nm on 13 March 2006 when the particles are formed by organic and kinetic nucleation. The ABL height is shown by black dotted horizontal line. (a) The shaded areas show the range of concentration when reaction rate of organics is multiplied by 0.2–1. (b) The shaded areas show the range of particle concentration when 2–10% of organic vapours can condense on particles (red) and when (i) organics are non-volatile, (ii) organics are non-volatile and P =10−3 cm−3 or (iii) organics cannot condense on particles below 3 nm (green). More details under Lauros et al., 2011.

Related recent publications from the group:

Boy, M., Hellmuth, O., Korhonen, H., Nillson, D., ReVelle, D., Turnipseed, A., Arnold, F. and Kulmala, M.: MALTE - Model to predict new aerosol formation in the lower troposphere, Atmos. Chem. Phys., 6, 4499-4517, 2006.

Siebert, H., Wehner, B., Hellmuth, O., Stratmann, F., Boy, M. and Klumala, M.: New-particle formation in connection with a nocturnal low-level jet: Observations and modeling results, Geophys. Res. Lett, 34, L16822, doi: 10.1029/2007GL029891, 2007.

Boy, M., Kazil, J., Lovejoy, E.R., Korhonen, H., Guenther, A. and Kulmala, M.: Relevance of ion-induced nucleation of sulphuric acid and water in the lower troposphere over the boreal forest at northern latitudes, Geophys. Res. Lett., doi:10.1016/j.atmosres.2008.01.002, 2008.

Lauros, J., Sogachev, A., Smolander, S., Vuollekoski, H., Sihto, S.-L., Laakso, L., Mammarella, I., Rannik, U. and Boy, M.: Particle concentration and flux dynamics in the atmospheric boundary layer as the indicator of formation mechanism, Atmos. Chem. Phys., 11, 5591-5691, 2011.

Ortega, K., Suni, T., Boy, M., Grönholm, T., Manninen, H.E., Nieminen, T., Ehn, M., Junninen, H., Hakola, H., Hellén, H., Valmari, T., Arvela, H., Zegelin, S., Hughes, D., Kitchen, M., Cleugh, H., Worsnop, D., Kulmala, M. and Kerminen, V.-M.: New insights into nocturnal nucleation, Atmos. Chem. Phys. Discuss., 11, 31323-31362, 2011.

SOSAA

SOSAA (model to Simulate the concentrations of Organic vapours, Sulphuric Acid and Aerosols, Boy et al., 2010) includes similar modules for emissions of organic vapours, gas phase chemistry and aerosol dynamics as MALTE. It is a one-dimensional parallelized model operating at the high-performance super cluster Murska at the CSC - IT Centre for Science in Espoo. SOSAA is the first model using a comprehensive aerosol dynamical code coupled with detailed chemistry and emissions to investigate the formation of secondary organic aerosols for longer periods (up to several years) with high vertical resolution.

Figure 4: Modelled monthly mean monoterpene concentrations for the year 2007 at SMEAR II, Hyytiälä, Finland using the emissions from Carene, Pinene and Intermediate chemotypes, and the average emission of the population. More details under Bäck et al., 2012.

Related publications from the group:

Boy, M., Sogachev, A., Lauros, J., Zhou, L., Guenther, A. and Smolander, S.: SOSA - a new model to simulate the concentrations of organic vapours and sulphuric acid inside the ABL - Part I: Model description and initial evaluation, Atmos. Chem. Phys. 11, 43-51, 2011.

Mogensen, D., Smolander, S., Sogachev, A., Zhou, L., Sinha, V., Guenther, A., Williams, J., Nieminen, T., Kajos, M., Rinne, J., Kulmala, M. and Boy, M.: Modelling atmospheric OH-reactivity in a boreal forest ecosystem, Atmos. Chem. Phys., 11, 9709-9719, 2011.

Kurtén, T., Zhou, L., Makkonen, R., Merikanto, J., Räisänen, P., Boy, M., Richards, N., Rap, A., Smolander, S., Sogachev, A., Guenther, A., Mann, G. W., Carslaw, K. and Kulmala, M.: Large methane releases lead to strong aerosol forcing and reduced cloudiness, Atmos. Chem. Phys. ,11, 6961-6969, 2011.

Bäck, J., Aalto, J., Henriksson, M., Hakola, H., He., Q. and Boy, M.: Chemodiversity in terpene emissions at a boreal Scots pine stand, Biogeosciences, 9, 689-702, 2012.

FLAMO

FLAMO is a flexible interface that provides an environment that is capable of coupling or integrating modules to study atmospheric processes in detail. To reduce computational time and expenses FLAMO is capable of using multi core clusters. FLAMO makes use of Message passing interface (MPI) that enables the code to run parallel in multi core clusters. Currently the Weather and Research Forecasting Model WRF runs offline with a refined domain size of one kilometer to predict the meteorological parameters. However, other models like large eddy simulation (LES) codes can be used (off- or online) to receive the requested input data. FLAMO is coupled with the emission, chemistry and aerosol dynamic modules already tested and evaluated in SOSAA. The FLAMO interface offers the user the possibility to study atmospheric processes with detailed chemistry, physics and flexible temporal and spatial resolutions. A first manuscript of the new developed model interface FLAMO will be published in late summer 2012.

PENCIL-CLOUD

The PENCIL code is a high-order finite-difference code for compressible hydrodynamic flows. It is highly modular and can easily be adapted to different types of problems. An aerosol dynamic module was implemented to study the effects of turbulence on the cloud formation processes (and vice versa) and to investigate the effects of different CCN- concentrations on the number of cloud droplets formed. This project started in the beginning of 2011 and a first manuscript is in preparation (“A study of aerosol production at the cloud edge with DNS”).

Figure 5: 2D distribution for different particle sizes in a turbulent flow regime. An accumulation of larger particles in the middle of the front and of smaller particles at the front edges is visible.

ECHAM - General circulation model of the atmosphere

Global aerosol modelling integrates observations, theories and results from box models to create a global scale picture of aerosol effects. Aerosols can be included in chemistry transport models or they can be coupled with a global climate model. Global models are computationally expensive, since computational domain can cover up to one billion grid cells. Hence descriptions of aerosol population and processes must be extensively simplified. We use ECHAM5-HAM global climate model (Stier et al., 2005) to study processes related to new particle formation. ECHAM5-HAM describes the most important atmospheric aerosol compounds, such as sulphate, black carbon, particulate organic matter, sea salt and dust, and can be easily modified for additional species.


Figure 6: Global 5-yr average cloud droplet number concentration for the pre-industrial, present-day and future conditions. The cloud droplet number concentration (CDNC) is sampled at the cloud-top height from simulations with (red) and without (black) nucleation. Error bars and corresponding shading indicate the range in CDNC due to different future anthropogenic emission pathways. Additional simulations with +50% biogenic VOC emissions (green) and +10% oceanic DMS emissions (blue) are simulated with the anthropogenic emission projection RCP 4.5. More details under Makkonen et al., 2012a.

Related publications from the group:

Kokkola, H., Korhonen, H., Lehtinen, K. E. J., Makkonen, R., Asmi, A., Järvenoja, S., Anttila, T., Partanen, A.-I., Kulmala, M., Järvinen, H., Laaksonen, A., and Kerminen, V.-M.: SALSA - a Sectional Aerosol module for Large Scale Applications, Atmos. Chem. Phys., 8, 2469-2483, 2008.

Makkonen, R., Asmi, A., Korhonen, H., Kokkola, H., Järvenoja, S., Räisänen, P., Lehtinen, K. E. J., Laaksonen, A., Kerminen, V.-M., Järvinen, H., Lohmann, U., Bennartz, R., Feichter, J., and Kulmala, M.: Sensitivity of aerosol concentrations and cloud properties to nucleation and secondary organic distribution in ECHAM5-HAM global circulation model, Atmos. Chem. Phys., 9, 1747-1766, 2009.

Makkonen, R., Asmi, A., Kerminen, V.-M., Boy, M., Arneth, A., Hari, P. and Kulmala, M.: Air pollution control and decreasing new particle formation lead to strong climate warming, Atmos. Chem. Phys., 12, 1515-1524,2012a.

Makkonen, R., Romakkaniemi, S. Kokkola, H., Stier, P., Räisänen, P., Rast, S., Feichter, J., Kulmala, M., and Laaksonen, A.: Brightening of the global cloud field by nitric acid and the associated radiative forcing, Atmos. Chem. Phys. Discuss., 12, 5225-5245, 2012b.

Makkonen, R., Asmi, A., Kerminen, V.-M., Boy, M., Arneth, A., Guenther, A. and Kulmala, M.: BVOC-aerosol-climate interactions studied with the global aerosol model ECHAM5.5- HAM2, Atmos. Chem. Phys. Discuss., 12, 9195-9246, 2012c.

Other References

Damian, V., Sandu, A., Damian, M., Potra, F., & Carmichael, G. R.: The Kinetic PreProcessor KPP -- A software environment for solving chemical kinetics, Computers and Chemical Engineering, 26 (11), 1567-1579, 2002.

Guenther, A., Karl, T., Harley, P., Wiedinmyer, C., Palmer, P. I., and Geron, C.: Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature), Atmos. Chem. Phys., 6, 3181-3210, 2006. http://www.atmos-chem-phys.net/6/3181/2006/acp-6-3181-2006.html

H. Korhonen, K. E. J. Lehtinen and M. Kulmala: Multicomponent aerosol dynamics model UHMA: Model development and validation, Atmos. Chem. Phys., 4, 757-771, 2004.

Sogachev, A., & Panferov, O.: Modification of two-equation models to account for plant drag, Boundary Layer Meteorology, 121, 229-266, 2006.

Sogachev, A., Menzhulin, G. V., Heimann, M., & Lloyd, J.: A simple three-dimensional canopy - planetary boundary layer simulation model for scalar concentrations and fluxes, Tellus B, 54 (5), 784-819, 2002.

Stier, P., Feichter, J., Kinne, S., Kloster, S., Vignati, E., Wilson, J., Ganzeveld, L., Tegen, I., Werner, M., Balkanski, Y., Schulz, M., Boucher, O., Minikin, A., and Petzold, A.: The aerosol-climate model ECHAM5-HAM, Atmos. Chem. Phys., 5, 1125-1156, 2005.