Continued development of a cloud droplet formation parameterization for global climate models

Fountoukis, C.; Nenes, Athanasios

doi:10.1029/2004jd005591

Cited by 273 publications

(527 citation statements)

References 31 publications

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“…In the most sophisticated parameterizations, CDNC is calculated based on aerosol particle size distribution and chemical composition, pressure, temperature and vertical velocity of air parcel forming the cloud (Abdul-Razzak et al, 1998;Ghan, 2000, 2002;Nenes and Seinfeld, 2003;Fountoukis and Nenes, 2005). The simulations in this study are conducted using the SALSA sectional aerosol model developed for atmospheric models (Kokkola et al, 2008;Bergman et al, 2012).…”

Section: Cloud Droplet Formation Parameterizationmentioning

confidence: 99%

Correction of approximation errors with Random Forests applied to modelling of cloud droplet formation

et al. 2013

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Abstract. In atmospheric models, due to their computational time or resource limitations, physical processes have to be simulated using reduced (i.e. simplified) models. The use of a reduced model, however, induces errors to the simulation results. These errors are referred to as approximation errors. In this paper, we propose a novel approach to correct these approximation errors. We model the approximation error as an additive noise process in the simulation model and employ the Random Forest (RF) regression algorithm for constructing a computationally low cost predictor for the approximation error. In this way, the overall simulation problem is decomposed into two separate and computationally efficient simulation problems: solution of the reduced model and prediction of the approximation error realisation. The approach is tested for handling approximation errors due to a reduced coarse sectional representation of aerosol size distribution in a cloud droplet formation calculation as well as for compensating the uncertainty caused by the aerosol activation parameterization itself. The results show a significant improvement in the accuracy of the simulation compared to the conventional simulation with a reduced model. The proposed approach is rather general and extension of it to different parameterizations or reduced process models that are coupled to geoscientific models is a straightforward task. Another major benefit of this method is that it can be applied to physical processes that are dependent on a large number of variables making them difficult to be parameterized by traditional methods.

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Section: Cloud Droplet Formation Parameterizationmentioning

confidence: 99%

Correction of approximation errors with Random Forests applied to modelling of cloud droplet formation

et al. 2013

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“…[30][31][32][33][34][35] All of these models serve to indicate the complex inter-relationships between aerosol Cloud droplets Aerosol particles of differing sizes and composition during the cloud droplet activation process. These complex interactions are the main reason why the indirect aerosol effect remains one of the key uncertainties regarding the impact of aerosol particles on the global climate.…”

Section: Activation Of Internally and Externally Mixed Aerosols In CLmentioning

confidence: 99%

Sea-salt particles and the CLAW hypothesis

Smith¹

2007

Environ. Chem.

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Environmental context. When proposing that dimethyl sulfide (DMS) releases from phytoplankton had a role in regulating the global climate, the potential parallel influences of sea spray aerosols on climate were largely disregarded. Over the intervening 20 years, scientific studies have clearly demonstrated a substantial role for sea spray particles in modifying cloud properties and influencing global sulfur cycling, diminishing the significance of the DMS-based CLAW mechanism.

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“…The most popular are those by Abdul-Razzak and Ghan and Fountoukis and Nenes (Fountoukis and Nenes, 2005). The former 45 was originally only tested up to a mean radius of 0.1 µm, which is where it shows some deviation from parcel model simulations.…”

mentioning

confidence: 99%

“…These condensed masses at cloud base are then used in the cloud activation scheme (Fountoukis and Nenes, 2005) in an analogous way to the equilibrium condensed masses in the single mode case . At low updrafts there is more time for the condensed masses to equilibrate 115 before activation resulting in the new dynamic parameterisation producing the same results as using the multiple mode equilibrium theory.…”

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A parameterisation for the co-condensation of semi-volatile organics into multiple aerosol particle modes

Crooks¹,

Connolly²,

McFiggans³

2017

Preprint

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Abstract.A new parameterisation for cloud droplet activation of multiple aerosol modes is presented that includes the effects of co-condensation of semi-volatile organic compounds (SVOCs). The novel work comes from the dynamic condensation parameterisation that approximates the partitioning of the SVOCs into the condensed phase at cloud base. The dynamic condensation parameterisation differs 5 from equilibrium absorptive partitioning theory by calculating time dependent condensed masses that depend on the updraft velocity. Additionally, more mass is placed on smaller particles than at equilibrium, which is in better agreement with parcel model simulations. All of the SVOCs with saturation concentrations below 1 × 10 −3 µg −3 are assumed to partition into the condensed phase at cloud base, defined as 100% relative humidity, and the dynamic condensation parameterisation is

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Continued development of a cloud droplet formation parameterization for global climate models

Cited by 273 publications

References 31 publications

Correction of approximation errors with Random Forests applied to modelling of cloud droplet formation

Correction of approximation errors with Random Forests applied to modelling of cloud droplet formation

Sea-salt particles and the CLAW hypothesis

A parameterisation for the co-condensation of semi-volatile organics into multiple aerosol particle modes

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