Atmospheric sulfur cycle simulated in the global model GOCART: Model description and global properties

Abstract. The Convective Cloud Field Model (CCFM) attempts to address some of the shortcomings of both the commonly used bulk mass-flux parameterisations and those using a prescribed spectrum of clouds. By considering the cloud spectrum as a competitive system in which cloud types interact through their environment in competition for convective available potential energy (CAPE), the spectrum is able to respond dynamically to changes in the environment. An explicit Lagrangian entraining plume model for each cloud type allows for the representation of convective-cloud microphysics, paving the way for the study of aerosol–convection interactions at the global scale where their impact remains highly uncertain. In this paper, we introduce a new treatment of convective triggering, extending the entraining plume model below cloud base to explicitly represent the unsaturated thermals which initiate convection. This allows for a realistic vertical velocity to develop at cloud base, so that the cloud microphysics can begin with physically based activation of cloud condensation nuclei (CCN). We evaluate this new version of CCFM in the context of the global model ECHAM6–HAM, comparing its performance to the standard Tiedtke–Nordeng parameterisation used in that model. We find that the spatio-temporal distribution of precipitation is improved, both against a climatology from the Global Precipitation Climatology Project (GPCP) and also against diurnal cycles from the Tropical Rainfall Measurement Mission (TRMM) with a reduced tendency for precipitation to peak too early in the afternoon. Cloud cover is quite sensitive to the vertical level from which the dry convection is initiated, but when this is chosen appropriately the cloud cover compares well with that from Tiedtke–Nordeng. CCFM can thus perform as well as, or better than, the standard scheme while providing additional capabilities to represent convective-cloud microphysics and dynamic cloud morphology at the global scale.

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DMS cycle in the marine ocean-atmosphere system – a global model study

Biogeosciences Discussions ◽

10.5194/bgd-2-1067-2005 ◽

2005 ◽

Vol 2 (4) ◽

pp. 1067-1126 ◽

Cited By ~ 4

Author(s):

S. Kloster ◽

J. Feichter ◽

E. Maier-Reimer ◽

K. D. Six ◽

P. Stier ◽

...

Keyword(s):

General Circulation ◽

Circulation Model ◽

Surface Concentration ◽

Ocean General Circulation Model ◽

Sulfur Cycle ◽

Biologically Active ◽

Sea Surface ◽

Aerosol Model ◽

Ocean Atmosphere ◽

Atmospheric Sulfur

Abstract. A global coupled ocean-atmosphere modeling system is established to study the production of Dimethylsulfide (DMS) in the ocean, the DMS flux to the atmosphere, and the resulting sulfur concentrations in the atmosphere. The DMS production and consumption processes in the ocean are simulated in the marine biogeochemistry model HAMOCC5, embedded in a ocean general circulation model (MPI-OM). The atmospheric model ECHAM5 is extended by the microphysical aerosol model HAM, treating the sulfur chemistry in the atmosphere and the evolution of the microphysically interacting internally- and externally mixed aerosol populations. We simulate a global annual mean DMS sea surface concentration of 1.8 nmol/l, a DMS emission of 28 Tg(S)/yr, a DMS burden in the atmosphere of 0.077 Tg(S), and a DMS lifetime of 1.0 days. To quantify the role of DMS in the atmospheric sulfur cycle we simulate the relative contribution of DMS-derived SO2 and SO4-2 to the total atmospheric sulfur concentrations. DMS contributes 25% to the global annually averaged SO2 column burden. For SO4-2 the contribution is 27%. The coupled model setup allows the evaluation of the simulated DMS quantities with measurements taken in the ocean and in the atmosphere. The simulated global distribution of DMS sea surface concentrations compares reasonably well with measurements. The comparison to SO4-2 surface concentration measurements in regions with a high DMS contribution to SO4-2 shows an overestimation by the model. This overestimation is most pronounced in the biologically active season with high DMS emissions and most likely caused by a too high simulated SO4-2 yield from DMS oxidation.

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Multi-Phase Processes in the Atmospheric Sulfur Cycle

Interactions of C, N, P and S Biogeochemical Cycles and Global Change ◽

10.1007/978-3-642-76064-8_13 ◽

1993 ◽

pp. 305-331 ◽

Cited By ~ 2

Author(s):

Jos Lelieveld

Keyword(s):

Sulfur Cycle ◽

Atmospheric Sulfur ◽

Multi Phase

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Anaerobic transformations of wastewater organic matter and sulfide production – investigations in a pilot plant pressure sewer

Water Science & Technology ◽

10.2166/wst.2002.0057 ◽

2002 ◽

Vol 45 (3) ◽

pp. 71-79 ◽

Cited By ~ 6

Author(s):

N. Tanaka ◽

T. Hvitved-Jacobsen

Keyword(s):

Organic Matter ◽

Wastewater Treatment ◽

Pilot Plant ◽

Process Model ◽

Wastewater Treatment Plants ◽

Model Simulation ◽

Sulfur Cycle ◽

Model Description ◽

Model Parameters ◽

Sulfide Production

Anaerobic transformations of wastewater organic matter and sulfide production rate were studied using a pilot plant pressure sewer (inner diameter: 102 mm, length: 47 m). Furthermore, a process model description including carbon and sulfur cycle was presented. Wastewater characterization based on oxygen utilization rate (OUR) measurement and VFA analysis was employed. Under anaerobic conditions, a net production of readily biodegradable substrate was observed, which fact is important for biological removal of nitrogen and phosphorus at subsequent wastewater treatment plants. Model parameters were determined on the basis of experimental findings. The model simulation of transformations of organic matter in sewers can be used as input to the model simulation and evaluation of the processes in wastewater treatment plants. The model is also useful to evaluate the problems in both sewers themselves and treatment plants caused by hydrogen sulfide.

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The atmospheric sulfur cycle over the Amazon Basin: 2. Wet season

Journal of Geophysical Research Atmospheres ◽

10.1029/jd095id10p16813 ◽

1990 ◽

Vol 95 (D10) ◽

pp. 16813 ◽

Cited By ~ 79

Author(s):

M. O. Andreae ◽

H. Berresheim ◽

H. Bingemer ◽

D. J. Jacob ◽

B. L. Lewis ◽

...

Keyword(s):

Amazon Basin ◽

Sulfur Cycle ◽

Wet Season ◽

Atmospheric Sulfur

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DMS cycle in the marine ocean-atmosphere system – a global model study

Biogeosciences ◽

10.5194/bg-3-29-2006 ◽

2006 ◽

Vol 3 (1) ◽

pp. 29-51 ◽

Cited By ~ 111

Author(s):

S. Kloster ◽

J. Feichter ◽

E. Maier-Reimer ◽

K. D. Six ◽

P. Stier ◽

...

Keyword(s):

General Circulation ◽

Circulation Model ◽

Surface Concentration ◽

Ocean General Circulation Model ◽

Sulfur Cycle ◽

Biologically Active ◽

Sea Surface ◽

Aerosol Model ◽

Ocean Atmosphere ◽

Atmospheric Sulfur

Abstract. A global coupled ocean-atmosphere modeling system is established to study the production of dimethylsulfide (DMS) in the ocean, the DMS flux to the atmosphere, and the resulting sulfur concentrations in the atmosphere. The DMS production and consumption processes in the ocean are simulated in the marine biogeochemistry model HAMOCC5, embedded in a ocean general circulation model (MPI-OM). The atmospheric model ECHAM5 is extended by the microphysical aerosol model HAM, treating the sulfur chemistry in the atmosphere and the evolution of the microphysically interacting internally- and externally mixed aerosol populations. We simulate a global annual mean DMS sea surface concentration of 1.8 nmol l−1, a DMS emission of 28 Tg(S) yr−1, a DMS burden in the atmosphere of 0.077 Tg(S), and a DMS lifetime of 1.0 days. To quantify the role of DMS in the atmospheric sulfur cycle we simulate the relative contribution of DMS-derived SO2 and SO42− to the total atmospheric sulfur concentrations. DMS contributes 25% to the global annually averaged SO2 column burden. For SO42− the contribution is 27%. The coupled model setup allows the evaluation of the simulated DMS quantities with measurements taken in the ocean and in the atmosphere. The simulated global distribution of DMS sea surface concentrations compares reasonably well with measurements. The comparison to SO42− surface concentration measurements in regions with a high DMS contribution to SO42− shows an overestimation by the model. This overestimation is most pronounced in the biologically active season with high DMS emissions and most likely caused by a too high simulated SO42− yield from DMS oxidation.

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